Journal articles: 'Biologically-inspired robots'

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Holland, Owen. "The first biologically inspired robots." Robotica 21, no. 4 (August 2003): 351–63. http://dx.doi.org/10.1017/s0263574703004971.

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Thie first biologically inspired robots, the famous electromechanical tortoises, were designed and built in 1949 by W. Grey Walter. This paper reviews their origins in Walter's theories of the brain and the nature of life, and uses contemporary unpublished notes and photographs to assess their significance then and now.

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Bekey, George A. "Biologically inspired control of autonomous robots." Robotics and Autonomous Systems 18, no. 1-2 (July 1996): 21–31. http://dx.doi.org/10.1016/0921-8890(96)00022-x.

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Wang, Hongqiang, Peter York, Yufeng Chen, Sheila Russo, Tommaso Ranzani, Conor Walsh, and Robert J. Wood. "Biologically inspired electrostatic artificial muscles for insect-sized robots." International Journal of Robotics Research 40, no. 6-7 (March 31, 2021): 895–922. http://dx.doi.org/10.1177/02783649211002545.

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Millimeter-sized electrostatic film actuators, inspired by the efficient spatial arrangement of insect muscles, achieve a muscle-like power density (61 W kg−1) and enable robotic applications in which agility is needed in confined spaces. Like biological muscles, these actuators incorporate a hierarchical structure, in this case building from electrodes to arrays to laminates, and are composed primarily of flexible materials. So comprised, these actuators can be designed for a wide range of manipulation and locomotion tasks, similar to natural muscle, while being robust and compact. A typical actuator can achieve 85 mN of force with a 15 mm stroke, with a size of [Formula: see text] mm3 and mass of 92 mg. Two millimeter-sized robots, an ultra-thin earthworm-inspired robot and an intestinal-muscle-inspired endoscopic tool for tissue resection, demonstrate the utility of these actuators. The earthworm robot undertakes inspection tasks: the navigation of a 5 mm channel and a 19 mm square tube while carrying an on-board camera. The surgical tool, which conforms to the surface of the distal end of an endoscope, similar to the thin, smooth muscle that covers the intestine, completes tissue cutting and penetrating tasks. Beyond these devices, we anticipate widespread use of these actuators in soft robots, medical robots, wearable robots, and miniature autonomous systems.

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Kelasidi, Eleni, Pal Liljeback, Kristin Y. Pettersen, and Jan Tommy Gravdahl. "Innovation in Underwater Robots: Biologically Inspired Swimming Snake Robots." IEEE Robotics & Automation Magazine 23, no. 1 (March 2016): 44–62. http://dx.doi.org/10.1109/mra.2015.2506121.

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Belter, Dominik, and Piotr Skrzypczyński. "A biologically inspired approach to feasible gait learning for a hexapod robot." International Journal of Applied Mathematics and Computer Science 20, no. 1 (March 1, 2010): 69–84. http://dx.doi.org/10.2478/v10006-010-0005-7.

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A biologically inspired approach to feasible gait learning for a hexapod robotThe objective of this paper is to develop feasible gait patterns that could be used to control a real hexapod walking robot. These gaits should enable the fastest movement that is possible with the given robot's mechanics and drives on a flat terrain. Biological inspirations are commonly used in the design of walking robots and their control algorithms. However, legged robots differ significantly from their biological counterparts. Hence we believe that gait patterns should be learned using the robot or its simulation model rather than copied from insect behaviour. However, as we have foundtahula rasalearning ineffective in this case due to the large and complicated search space, we adopt a different strategy: in a series of simulations we show how a progressive reduction of the permissible search space for the leg movements leads to the evolution of effective gait patterns. This strategy enables the evolutionary algorithm to discover proper leg co-ordination rules for a hexapod robot, using only simple dependencies between the states of the legs and a simple fitness function. The dependencies used are inspired by typical insect behaviour, although we show that all the introduced rules emerge also naturally in the evolved gait patterns. Finally, the gaits evolved in simulations are shown to be effective in experiments on a real walking robot.

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Zhang, Chi, Wei Zou, Liping Ma, and Zhiqing Wang. "Biologically inspired jumping robots: A comprehensive review." Robotics and Autonomous Systems 124 (February 2020): 103362. http://dx.doi.org/10.1016/j.robot.2019.103362.

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Shahbazi, Hamed, Kamal Jamshidi, Amir Hasan Monadjemi, and Hafez Eslami. "Biologically inspired layered learning in humanoid robots." Knowledge-Based Systems 57 (February 2014): 8–27. http://dx.doi.org/10.1016/j.knosys.2013.12.003.

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Bar-Cohen, Y. "Biologically Inspired Intelligent Robots using Artificial Muscles." Strain 41, no. 1 (February 2005): 19–24. http://dx.doi.org/10.1111/j.1475-1305.2004.00161.x.

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Masár, Marek, and Ivana Budinská. "Robot Coordination Based on Biologically Inspired Methods." Advanced Materials Research 664 (February 2013): 891–96. http://dx.doi.org/10.4028/www.scientific.net/amr.664.891.

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An embedded particle swarm optimization (PSO) technique combined with virtual pheromones deposition and rules for artificial bird flocking is proposed to handle an area coverage problem using a swarm of mobile robots. A simulation tool VERA that was developed to simulate a swarm behavior of a group of mobile agents is described. Results of simulation experiments and tests on Lego robots that prove the concept are presented. Results are discussed and future development is suggested in the end of the paper.

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Parker, Chris A. C., and Hong Zhang. "Biologically inspired collective comparisons by robotic swarms." International Journal of Robotics Research 30, no. 5 (March 7, 2011): 524–35. http://dx.doi.org/10.1177/0278364910397621.

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Intelligent entities must often make decisions by comparing several candidate alternatives and selecting the best one. This is just as true for autonomous swarms as it is for solitary robots, but to date there has been little work to propose efficient comparison behaviors for autonomous robotic swarms that are not tied to specific environments. In this work, we examine an elegant collective comparison strategy that is used by at least three different species of social insect and adapt it for artificial systems. The behavior is particularly attractive for robotic implementations because it relies only on short range explicit peer-to-peer communication, eliminating the need for chemical trails or other forms of stigmergy. The proposed comparison strategy is proven to converge, and a series of experiments using real robots with noisy sensors is presented that validates our theoretical analysis. Using the proposed behavior, a robotic swarm is able to compare alternatives collectively more accurately than its member robots would be able to individually.

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Kimura, Hiroshi, Yasuhiro Fukuoka, and Avis H. Cohen. "Biologically inspired adaptive walking of a quadruped robot." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 365, no. 1850 (November 17, 2006): 153–70. http://dx.doi.org/10.1098/rsta.2006.1919.

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We describe here the efforts to induce a quadruped robot to walk with medium-walking speed on irregular terrain based on biological concepts. We propose the necessary conditions for stable dynamic walking on irregular terrain in general, and we design the mechanical and the neural systems by comparing biological concepts with those necessary conditions described in physical terms. PD-controller at joints constructs the virtual spring–damper system as the viscoelasticity model of a muscle. The neural system model consists of a central pattern generator (CPG), reflexes and responses. We validate the effectiveness of the proposed neural system model control using the quadruped robots called ‘Tekken1&2’. MPEG footage of experiments can be seen at http://www.kimura.is.uec.ac.jp .

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Sareh, Sina, Kaspar Althoefer, Min Li, Yohan Noh, Francesca Tramacere, Pooya Sareh, Barbara Mazzolai, and Mirko Kovac. "Anchoring like octopus: biologically inspired soft artificial sucker." Journal of The Royal Society Interface 14, no. 135 (October 2017): 20170395. http://dx.doi.org/10.1098/rsif.2017.0395.

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This paper presents a robotic anchoring module, a sensorized mechanism for attachment to the environment that can be integrated into robots to enable or enhance various functions such as robot mobility, remaining on location or its ability to manipulate objects. The body of the anchoring module consists of two portions with a mechanical stiffness transition from hard to soft. The hard portion is capable of containing vacuum pressure used for actuation while the soft portion is highly conformable to create a seal to contact surfaces. The module is integrated with a single sensory unit which exploits a fibre-optic sensing principle to seamlessly measure proximity and tactile information for use in robot motion planning as well as measuring the state of firmness of its anchor. In an experiment, a variable set of physical loads representing the weights of potential robot bodies were attached to the module and its ability to maintain the anchor was quantified under constant and variable vacuum pressure signals. The experiment shows the effectiveness of the module in quantifying the state of firmness of the anchor and discriminating between different amounts of physical loads attached to it. The proposed anchoring module can enable many industrial and medical applications where attachment to environment is of crucial importance for robot control.

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Yang, Woosung, Hyungjoo Kim, and Bum Jae You. "Biologically Inspired Self-Stabilizing Control for Bipedal Robots." International Journal of Advanced Robotic Systems 10, no. 2 (February 2013): 144. http://dx.doi.org/10.5772/55463.

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Solis, Jorge, Kenichiro Ozawa, Maasaki Takeuchi, Takafumi Kusano, Shimpei Ishikawa, Klaus Petersen, and Atsuo Takanishi. "Biologically-Inspired Control Architecture for Musical Performance Robots." International Journal of Advanced Robotic Systems 11, no. 10 (January 2014): 172. http://dx.doi.org/10.5772/59232.

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Kelasidi, Eleni, Mansoureh Jesmani, Kristin Pettersen, and Jan Gravdahl. "Locomotion Efficiency Optimization of Biologically Inspired Snake Robots." Applied Sciences 8, no. 1 (January 9, 2018): 80. http://dx.doi.org/10.3390/app8010080.

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Couceiro, Micael S., J. Miguel A. Luz, Carlos M. Figueiredo, and N. M. Fonseca Ferreira. "Modeling and control of biologically inspired flying robots." Robotica 30, no. 1 (April 27, 2011): 107–21. http://dx.doi.org/10.1017/s0263574711000312.

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SUMMARYThis paper covers a wide knowledge of physical and dynamical models useful for building flying robots and a new generation of flying platform developed in the similarity of flying animals. The goal of this work is to develop a simulation environment and dynamic control using the high-level calculation tool MatLab and the modeling, simulation, and analysis of dynamic systems tool Simulink. Once created the dynamic models to study, this work involves the study and understanding of the dynamic stability criteria to be adopted and their potential use in the control of flying models.

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Fernández-Caballero, Antonio. "Biologically Inspired Vision Systems for Flying Robots – Editorial." International Journal of Advanced Robotic Systems 13, no. 1 (January 2016): 22. http://dx.doi.org/10.5772/62432.

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Sheng-Dong Xu, Sendren, Hsu-Chih Huang, Tai-Chun Chiu, and Shao-Kang Lin. "Biologically-Inspired Learning and Adaptation of Self-Evolving Control for Networked Mobile Robots." Applied Sciences 9, no. 5 (March 12, 2019): 1034. http://dx.doi.org/10.3390/app9051034.

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This paper presents a biologically-inspired learning and adaptation method for self-evolving control of networked mobile robots. A Kalman filter (KF) algorithm is employed to develop a self-learning RBFNN (Radial Basis Function Neural Network), called the KF-RBFNN. The structure of the KF-RBFNN is optimally initialized by means of a modified genetic algorithm (GA) in which a Lévy flight strategy is applied. By using the derived mathematical kinematic model of the mobile robots, the proposed GA-KF-RBFNN is utilized to design a self-evolving motion control law. The control parameters of the mobile robots are self-learned and adapted via the proposed GA-KF-RBFNN. This approach is extended to address the formation control problem of networked mobile robots by using a broadcast leader-follower control strategy. The proposed pragmatic approach circumvents the communication delay problem found in traditional networked mobile robot systems where consensus graph theory and directed topology are applied. The simulation results and numerical analysis are provided to demonstrate the merits and effectiveness of the developed GA-KF-RBFNN to achieve self-evolving formation control of networked mobile robots.

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Trimmer, Barry Andrew. "Metal or muscle? The future of biologically inspired robots." Science Robotics 5, no. 38 (January 22, 2020): eaba6149. http://dx.doi.org/10.1126/scirobotics.aba6149.

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Clark, Jonathan E., and Mark R. Cutkosky. "The Effect of Leg Specialization in a Biomimetic Hexapedal Running Robot." Journal of Dynamic Systems, Measurement, and Control 128, no. 1 (December 1, 2005): 26–35. http://dx.doi.org/10.1115/1.2168477.

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The biologically inspired Sprawl family of hexapedal robots has shown that fast and stable running is possible with only open-loop control. Proper design of the passively self-stabilizing leg structure has enabled these robots to run at speeds of up to 15 bodylengths/s and over uneven terrain. Unlike other running robots built to date, the Sprawl robots’ front and rear legs are designed to preform distinct functional roles. Like the cockroaches that inspired them, the front legs of the robots act to lift and decelerate, while the rear legs provide the primary forward thrust. This paper uses a dynamic simulation to investigate the effect that changing the robot’s leg structure and posture has on its performance. The simulation results support our hypothesis that the use of a differential leg function induced through postural adjustments effectively trades efficiency for stability.

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Santana, Pedro F., José Barata, and Luís Correia. "Sustainable Robots for Humanitarian Demining." International Journal of Advanced Robotic Systems 4, no. 2 (June 1, 2007): 23. http://dx.doi.org/10.5772/5695.

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This paper proposes a roadmap for the application of advanced technology (in particular robotics) for the humanitarian demining domain. Based on this roadmap, a portable demining kit to handle urgent situations in remote locations is described. A low-cost four-wheel steering robot with a biologically inspired locomotion control is the base of the kit. On going research on a method for all-terrain piloting, under the morphological computation paradigm is also introduced, along with the behavioural architecture underlying it, the Survival Kit. A multi-agent architecture, the DSAAR architecture, is also proposed as a way of promoting short time-to-market and soft integration of different robots in a given mission. A common denominator for all developments is the quest for sustainability with respect to (re-)engineering and maintainability effort, as well as economical and ecological impact. Failing to cope with these requirements greatly reduces the applicability of a given technology to the humanitarian demining domain. Finally it is concluded that biologically inspired design fits considerably well to support a sustainable demining paradigm.

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Martinez-Martin, Ester, and Angel P. del Pobil. "A Biologically Inspired Approach for Robot Depth Estimation." Computational Intelligence and Neuroscience 2018 (August 23, 2018): 1–16. http://dx.doi.org/10.1155/2018/9179462.

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Aimed at building autonomous service robots, reasoning, perception, and action should be properly integrated. In this paper, the depth cue has been analysed as an early stage given its importance for robotic tasks. So, from neuroscience findings, a hierarchical four-level dorsal architecture has been designed and implemented. Mainly, from a stereo image pair, a set of complex Gabor filters is applied for estimating an egocentric quantitative disparity map. This map leads to a quantitative depth scene representation that provides the raw input for a qualitative approach. So, the reasoning method infers the data required to make the right decision at any time. As it will be shown, the experimental results highlight the robust performance of the biologically inspired approach presented in this paper.

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Kinugasa, Tetsuya, Koh Hosoda, Masatsugu Iribe, Fumihiko Asano, and Yasuhiro Sugimoto. "Special Issue on Dynamically and Biologically Inspired Legged Locomotion." Journal of Robotics and Mechatronics 29, no. 3 (June 20, 2017): 455. http://dx.doi.org/10.20965/jrm.2017.p0455.

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Legged locomotion, including walking, running, turning, and jumping, strongly depends on the dynamics and biological characteristics of the body involved. Gait patterns and energy efficiency, for example, are known to be greatly affected by not only travel velocity and ground contact conditions but also by body configuration, such as joint stiffness and coordination, as well as foot sole shape. To understand legged locomotion principles, we must clarify how the body’s dynamic and biological characteristics affect locomotion. Effort must also be made to incorporate these characteristics inventively to improve locomotion performance, such as robustness, adaptability, and efficiency, which further refine the legged locomotion. This special issue on “Dynamically and Biologically Inspired Legged Locomotion,” studies on legged locomotion based on dynamic and biological characteristics, covers a wide range of themes, such as a rimless wheel, a design method for a biped based on passive dynamic walking, the analysis of biped locomotion based on passive dynamic walking and dynamically inspired walking, an analysis of gait generation for a triped robot, and quadruped locomotion with a flexible trunk. Since there are interesting papers on legged robots with different numbers of legs, we basically organized the papers based on the number of legs. Studies on “Dynamically and Biologically Inspired Legged Locomotion” are expected to not only realize and improve legged locomotion as engineering, but also to reveal the locomotion mechanism of various creatures as science.

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Yun Seong Song and M. Sitti. "Surface-Tension-Driven Biologically Inspired Water Strider Robots: Theory and Experiments." IEEE Transactions on Robotics 23, no. 3 (June 2007): 578–89. http://dx.doi.org/10.1109/tro.2007.895075.

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Chirikjian, Gregory S. "Design and analysis of some nonanthropomorphic, biologically inspired robots: An overview." Journal of Robotic Systems 18, no. 12 (2001): 701–13. http://dx.doi.org/10.1002/rob.8108.

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Hsieh, M. Ani, Ádám Halász, Spring Berman, and Vijay Kumar. "Biologically inspired redistribution of a swarm of robots among multiple sites." Swarm Intelligence 2, no. 2-4 (September 10, 2008): 121–41. http://dx.doi.org/10.1007/s11721-008-0019-z.

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Sugisaka, Masanori, Kouta Imamura, Kouji Tokuda, and Maoki Masuda. "A new artificial life body: biologically inspired dynamic bipedal humanoid robots." Artificial Life and Robotics 8, no. 1 (September 2004): 1–4. http://dx.doi.org/10.1007/s10015-004-0307-7.

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DallaLibera, Fabio, Shuhei Ikemoto, Hiroshi Ishiguro, and Koh Hosoda. "Control of real-world complex robots using a biologically inspired algorithm." Artificial Life and Robotics 17, no. 1 (July 27, 2012): 42–46. http://dx.doi.org/10.1007/s10015-012-0034-4.

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Ide, Shoichiro, and Atsushi Nishikawa. "Muscle Coordination Control for an Asymmetrically Antagonistic-Driven Musculoskeletal Robot Using Attractor Selection." Applied Bionics and Biomechanics 2018 (September 12, 2018): 1–10. http://dx.doi.org/10.1155/2018/9737418.

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Recently, numerous musculoskeletal robots have been developed to realize the flexibility and dexterity analogous to human beings and animals. However, because the arrangement of many actuators is complex, the design of the control system for the robot is difficult and challenging. We believe that control methods inspired by living things are important in the development of the control systems for musculoskeletal robots. In this study, we propose a muscle coordination control method using attractor selection, a biologically inspired search method, for an antagonistic-driven musculoskeletal robot in which various muscles (monoarticular muscles and a polyarticular muscle) are arranged asymmetrically. First, muscle coordination control models for the musculoskeletal robot are built using virtual antagonistic muscle structures with a virtually symmetric muscle arrangement. Next, the attractor selection is applied to the control model and subsequently applied to the previous control model without muscle coordination to compare the control model’s performance. Finally, position control experiments are conducted, and the effectiveness of the proposed muscle coordination control and the virtual antagonistic muscle structure is evaluated.

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HESSE, FRANK, and FLORENTIN WÖRGÖTTER. "A GOAL-ORIENTATION FRAMEWORK FOR SELF-ORGANIZING CONTROL." Advances in Complex Systems 16, no. 02n03 (May 2013): 1350002. http://dx.doi.org/10.1142/s0219525913500021.

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Self-organization, especially in the framework of embodiment in biologically inspired robots, allows the acquisition of behavioral primitives by autonomous robots themselves. However, it is an open question how self-organization of basic motor primitives and goal-orientation can be combined, which is a prerequisite for the usefulness of such systems. In the paper at hand we propose a goal-orientation framework allowing the combination of self-organization and goal-orientation for the control of autonomous robots in a mutually independent fashion. Self-organization based motor primitives are employed to achieve a given goal. This requires less initial knowledge about the properties of robot and environment and increases adaptivity of the overall system. A combination of self-organization and reward-based learning seems thus a promising route for the development of adaptive learning systems.

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Andrade, Gabriela R., and Jordan H. Boyle. "A minimal biologically-inspired algorithm for robots foraging energy in uncertain environments." Robotics and Autonomous Systems 128 (June 2020): 103499. http://dx.doi.org/10.1016/j.robot.2020.103499.

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Low, Emily M. P., Ian R. Manchester, and Andrey V. Savkin. "A biologically inspired method for vision-based docking of wheeled mobile robots." Robotics and Autonomous Systems 55, no. 10 (October 2007): 769–84. http://dx.doi.org/10.1016/j.robot.2007.04.002.

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Arena, Paolo, Davide Lombardo, and Luca Patanè. "Biorobots, Nonlinear Dynamics and Perception." Advances in Science and Technology 58 (September 2008): 143–52. http://dx.doi.org/10.4028/www.scientific.net/ast.58.143.

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In this contribution a survey on a novel approach to locomotion and perception in biologically inspired robots is presented. The basic electronic architecture for modeling and implementing nonlinear dynamics involved in motion and perceptual control of the robot is the Cellular nonlinear network paradigm. It is shown how this continuous time lattice of neural-like circuits can generate suitable and real-time dynamics for efficient control of multi-actuators moving machines, and also to create the basis for a perceptual control of their behaviors.

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OKITA, SANDRA Y., and DANIEL L. SCHWARTZ. "YOUNG CHILDREN'S UNDERSTANDING OF ANIMACY AND ENTERTAINMENT ROBOTS." International Journal of Humanoid Robotics 03, no. 03 (September 2006): 393–412. http://dx.doi.org/10.1142/s0219843606000795.

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Complex interactions, biologically-inspired features and intelligence are increasingly seen in entertainment robots. Do these features affect how children interpret robots? Children have "animistic intuitions" that they use to attribute intelligence, biology, and agency to living things. Two studies explore whether young children also apply animistic intuitions to robotic animals, and whether attributes vary by the child's age, robot behavior and appearance. A total of ninety-three three- to five-year-olds participated in two experiments. They observed or interacted with robots that exhibited different behaviors and levels of responsiveness to their environment. They then answered simple questions that probed their attributions of biology, intelligence, and agency. The results indicated that regardless of the robots' look and behavior, younger children over-generalized their animistic intuitions about real animals and older children attributed some animistic qualities but not others. One implication is that young children's criteria and attributions do not depend on robot features that are important for older children and adults. Another implication is that children do not have a theory of aliveness, and they develop the category of robot slowly and piecemeal as they learn discrete facts about how technology differs from living things.

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Transeth, Aksel Andreas, Kristin Ytterstad Pettersen, and Pål Liljebäck. "A survey on snake robot modeling and locomotion." Robotica 27, no. 7 (March 3, 2009): 999–1015. http://dx.doi.org/10.1017/s0263574709005414.

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SUMMARYSnake robots have the potential to make substantial contributions in areas such as rescue missions, firefighting, and maintenance where it may either be too narrow or too dangerous for personnel to operate. During the last 10–15 years, the published literature on snake robots has increased significantly. The purpose of this paper is to give a survey of the various mathematical models and motion patterns presented for snake robots. Both purely kinematic models and models including dynamics are investigated. Moreover, the different approaches to biologically inspired locomotion and artificially generated motion patterns for snake robots are discussed.

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Yao, Jianjun, Shuang Gao, Guilin Jiang, Thomas L. Hill, Han Yu, and Dong Shao. "Screw theory based motion analysis for an inchworm-like climbing robot." Robotica 33, no. 08 (April 29, 2014): 1704–17. http://dx.doi.org/10.1017/s0263574714001003.

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SUMMARYTo obtain better performance on unstructured environments, such as in agriculture, forestry, and high-altitude operations, more and more researchers and engineers incline to study classes of biologically inspired robots. Since the natural inchworm can move well in various types of terrain, inchworm-like robots can exhibit excellent mobility. This paper describes a novel inchworm-type robot with simple structure developed for the application for climbing on trees or poles with a certain range of diameters. Modularization is adopted in the robot configuration. The robot is a serial mechanism connected by four joint modules and two grippers located at the front and rear end, respectively. Each joint is driven by servos, and each gripper is controlled by a linear motor. The simplified mechanism model is established, and then is used for its kinematic analysis based on screw theory. The dynamics of the robot are also analyzed by using Lagrange equations. The simulation of the robot gait imitating the locomotion of real inchworm is finally presented.

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Lewinger, William A., Cynthia M. Harley, Michael S. Watson, Michael S. Branicky, Roy E. Ritzmann, and Roger D. Quinn. "Animal-Inspired Sensing for Autonomously Climbing or Avoiding Obstacles." Applied Bionics and Biomechanics 6, no. 1 (2009): 43–61. http://dx.doi.org/10.1155/2009/280968.

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The way that natural systems navigate their environments with agility, intelligence and efficiency is an inspiration to engineers. Biological attributes such as modes of locomotion, sensory modalities, behaviours and physical appearance have been used as design goals. While methods of locomotion allow robots to move through their environment, the addition of sensing, perception and decision making are necessary to perform this task with autonomy. This paper contrasts how the addition of two separate sensing modalities – tactile antennae and non-contact sensing – and a low-computation, capable microcontroller allow a biologically abstracted mobile robot to make insect-inspired decisions when encountering a shelflike obstacle, navigating a cluttered environment without collision and seeking vision-based goals while avoiding obstacles.

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Moualla, Aliaa, Sofiane Boucenna, Ali Karaouzene, Denis Vidal, and Philippe Gaussier. "Is it useful for a robot to visit a museum?" Paladyn, Journal of Behavioral Robotics 9, no. 1 (December 1, 2018): 374–90. http://dx.doi.org/10.1515/pjbr-2018-0025.

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AbstractIn this work, we study how learning in a special environment such as a museum can influence the behavior of robots. More specifically, we show that online learning based on interaction with people at a museum leads the robots to develop individual preferences. We first developed a humanoid robot (Berenson) that has the ability to head toward its preferred object and to make a facial expression that corresponds to its attitude toward said object. The robot is programmed with a biologically-inspired neural network sensory-motor architecture. This architecture allows Berenson to learn and to evaluate objects. During experiments, museum visitors’ emotional responses to artworks were recorded and used to build a database for training. A similar database was created in the laboratory with laboratory objects. We use those databases to train two simulated populations of robots. Each simulated robot emulates the Berenson sensory-motor architecture. Firstly, the results show the good performance of our architecture in artwork recognition in the museum. Secondly, they demonstrate the effect of training variability on preference diversity. The response of the two populations in a new unknown environment is different; the museum population of robots shows a greater variance in preferences than the population of robots that have been trained only on laboratory objects. The obtained diversity increases the chances of success in an unknown environment and could favor an accidental discovery.

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Chang, Alexander H., and Patricio A. Vela. "Evaluation of Bio-Inspired Scales on Locomotion Performance of Snake-Like Robots." Robotica 37, no. 08 (February 5, 2019): 1302–19. http://dx.doi.org/10.1017/s0263574718001522.

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SummaryThe unique frictional properties conferred by snake ventral scales inspired the engineering and fabrication of surrogate mechanisms for a robotic snake. These artificial, biologically inspired scales produce anisotropic body-ground forcing patterns with various locomotion surfaces. The benefits they confer to robotic snake-like locomotion were evaluated in experimental trials employing rectilinear, lateral undulation, and sidewinding gaits over several distinct surface types: carpet, inhomogeneous concrete and homogeneous concrete. Enhanced locomotive performance, with respect to net displacement and heading stability, was consistently measured in scenarios that utilized the engineered scales, over equivalent scenarios where the anisotropic effects of scales were absent.

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Song, Changhui, and Weicheng Cui. "Review of Underwater Ship Hull Cleaning Technologies." Journal of Marine Science and Application 19, no. 3 (September 2020): 415–29. http://dx.doi.org/10.1007/s11804-020-00157-z.

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Abstract This paper presents a comprehensive review and analysis of ship hull cleaning technologies. Various cleaning methods and devices applied to dry-dock cleaning and underwater cleaning are introduced in detail, including rotary brushes, high-pressure and cavitation water jet technology, ultrasonic technology, and laser cleaning technology. The application of underwater robot technology in ship cleaning not only frees divers from engaging in heavy work but also creates safe and efficient industrial products. Damage to the underlying coating of the ship caused by the underwater cleaning operation can be minimized by optimizing the working process of the underwater cleaning robot. With regard to the adhesion technology mainly used in underwater robots, an overview of recent developments in permanent magnet and electromagnetic adhesion, negative pressure force adhesion, thrust force adhesion, and biologically inspired adhesion is provided. Through the analysis and comparison of current underwater robot products, this paper predicts that major changes in the application of artificial intelligence and multirobot cooperation, as well as optimization and combination of various technologies in underwater cleaning robots, could be expected to further lead to breakthroughs in developing next-generation robots for underwater cleaning.

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Cuneo, J., L. Barboni, N. Blanco, M. del Castillo, and J. Quagliotti. "ARM-Cortex M3-Based Two-Wheel Robot for Assessing Grid Cell Model of Medial Entorhinal Cortex: Progress towards Building Robots with Biologically Inspired Navigation-Cognitive Maps." Journal of Robotics 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/8069654.

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This article presents the implementation and use of a two-wheel autonomous robot and its effectiveness as a tool for studying the recently discovered use of grid cells as part of mammalian’s brains space-mapping circuitry (specifically the medial entorhinal cortex). A proposed discrete-time algorithm that emulates the medial entorhinal cortex is programed into the robot. The robot freely explores a limited laboratory area in the manner of a rat or mouse and reports information to a PC, thus enabling research without the use of live individuals. Position coordinate neural maps are achieved as mathematically predicted although for a reduced number of implemented neurons (i.e., 200 neurons). However, this type of computational embedded system (robot’s microcontroller) is found to be insufficient for simulating huge numbers of neurons in real time (as in the medial entorhinal cortex). It is considered that the results of this work provide an insight into achieving an enhanced embedded systems design for emulating and understanding mathematical neural network models to be used as biologically inspired navigation system for robots.

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Nurmaini, Siti, and Bambang Tutuko. "Intelligent Robotics Navigation System: Problems, Methods, and Algorithm." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (December 1, 2017): 3711. http://dx.doi.org/10.11591/ijece.v7i6.pp3711-3726.

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This paper set out to supplement new studies with a brief and comprehensible review of the advanced development in the area of the navigation system, starting from a single robot, multi-robot, and swarm robots from a particular perspective by taking insights from these biological systems. The inspiration is taken from nature by observing the human and the social animal that is believed to be very beneficial for this purpose. The intelligent navigation system is developed based on an individual characteristic or a social animal biological structure. The discussion of this paper will focus on how simple agent’s structure utilizes flexible and potential outcomes in order to navigate in a productive and unorganized surrounding. The combination of the navigation system and biologically inspired approach has attracted considerable attention, which makes it an important research area in the intelligent robotic system. Overall, this paper explores the implementation, which is resulted from the simulation performed by the embodiment of robots operating in real environments.

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Piltan, Farzin, Cheol-Hong Kim, and Jong-Myon Kim. "Adaptive Fuzzy-Based Fault-Tolerant Control of a Continuum Robotic System for Maxillary Sinus Surgery." Applied Sciences 9, no. 12 (June 19, 2019): 2490. http://dx.doi.org/10.3390/app9122490.

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Continuum robots represent a class of highly sensitive, multiple-degrees-of-freedom robots that are biologically inspired. Because of their flexibility and accuracy, these robots can be used in maxillary sinus surgery. The design of an effective procedure with high accuracy, reliability, robust fault diagnosis, and fault-tolerant control for a surgical robot for the sinus is necessary to maintain the high performance and safety necessary for surgery on the maxillary sinus. Thus, a robust adaptive hybrid observation method using an adaptive, fuzzy auto regressive with exogenous input (ARX) Laguerre Takagi–Sugeno (T–S) fuzzy robust feedback linearization observer for a surgical robot is presented. To address the issues of system modeling, the fuzzy ARX-Laguerre technique is represented. In addition, a T–S fuzzy robust feedback linearization observer is applied to a fuzzy ARX-Laguerre to improve the accuracy of fault estimation, reliability, and robustness for the surgical robot in the presence of uncertainties. For fault-tolerant control in the presence of uncertainties and unknown conditions, an adaptive fuzzy observation-based feedback linearization technique is presented. The effectiveness of the proposed algorithm is tested with simulations. Experimental results show that the proposed method reduces the average position error from 35 mm to 2.45 mm in the presence of faults.

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Breazeal, Cynthia, Daphna Buchsbaum, Jesse Gray, David Gatenby, and Bruce Blumberg. "Learning From and About Others: Towards Using Imitation to Bootstrap the Social Understanding of Others by Robots." Artificial Life 11, no. 1-2 (January 2005): 31–62. http://dx.doi.org/10.1162/1064546053278955.

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We want to build robots capable of rich social interactions with humans, including natural communication and cooperation. This work explores how imitation as a social learning and teaching process may be applied to building socially intelligent robots, and summarizes our progress toward building a robot capable of learning how to imitate facial expressions from simple imitative games played with a human, using biologically inspired mechanisms. It is possible for the robot to bootstrap from this imitative ability to infer the affective reaction of the human with whom it interacts and then use this affective assessment to guide its subsequent behavior. Our approach is heavily influenced by the ways human infants learn to communicate with their caregivers and come to understand the actions and expressive behavior of others in intentional and motivational terms. Specifically, our approach is guided by the hypothesis that imitative interactions between infant and caregiver, starting with facial mimicry, are a significant stepping-stone to developing appropriate social behavior, to predicting others' actions, and ultimately to understanding people as social beings.

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Su, Hang, Nima Enayati, Luca Vantadori, Andrea Spinoglio, Giancarlo Ferrigno, and Elena De Momi. "Online human-like redundancy optimization for tele-operated anthropomorphic manipulators." International Journal of Advanced Robotic Systems 15, no. 6 (November 1, 2018): 172988141881469. http://dx.doi.org/10.1177/1729881418814695.

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Robot human-like behavior can enhance the performance of human–robot cooperation with prominently improved natural interaction. This also holds for redundant robots with an anthropomorphic kinematics. In this article, we translated human ability of managing redundancy to control a seven degrees of freedom anthropomorphic robot arm (LWR4+, KUKA, Germany) during tele-operated tasks. We implemented a nonlinear regression method—based on neural networks—between the human arm elbow swivel angle and the hand target pose to achieve an anthropomorphic arm posture during tele-operation tasks. The method was assessed in simulation and experiments were performed with virtual reality tracking tasks in a lab environment. The results showed that the robot achieves a human-like arm posture during tele-operation, and the subjects prefer to work with the biologically inspired robot. The proposed method can be applied in control of anthropomorphic robot manipulators for tele-operated collaborative tasks, such as in factories or in operating rooms.

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Sloman, A., and R. L. Chrisley. "More things than are dreamt of in your biology: Information-processing in biologically inspired robots." Cognitive Systems Research 6, no. 2 (June 2005): 145–74. http://dx.doi.org/10.1016/j.cogsys.2004.06.004.

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Maroto-Gómez, Marcos, Álvaro Castro-González, José Castillo, María Malfaz, and Miguel Salichs. "A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User." Sensors 18, no. 8 (August 16, 2018): 2691. http://dx.doi.org/10.3390/s18082691.

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Nowadays, many robotic applications require robots making their own decisions and adapting to different conditions and users. This work presents a biologically inspired decision making system, based on drives, motivations, wellbeing, and self-learning, that governs the behavior of the robot considering both internal and external circumstances. In this paper we state the biological foundations that drove the design of the system, as well as how it has been implemented in a real robot. Following a homeostatic approach, the ultimate goal of the robot is to keep its wellbeing as high as possible. In order to achieve this goal, our decision making system uses learning mechanisms to assess the best action to execute at any moment. Considering that the proposed system has been implemented in a real social robot, human-robot interaction is of paramount importance and the learned behaviors of the robot are oriented to foster the interactions with the user. The operation of the system is shown in a scenario where the robot Mini plays games with a user. In this context, we have included a robust user detection mechanism tailored for short distance interactions. After the learning phase, the robot has learned how to lead the user to interact with it in a natural way.

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Hopkins, Michael, Robert Griffin, and Alexander Leonessa. "Compliant Locomotion." Mechanical Engineering 137, no. 06 (June 1, 2015): S12—S16. http://dx.doi.org/10.1115/1.2015-jun-6.

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This article describes benefits of model-based approach in developing humanoids and presents experimental results as well. Regardless of the chosen actuation strategy, the design of humanoid locomotion controllers is greatly complicated by the underactuated and nonlinear nature of the associated multibody dynamics. Drawing inspiration from biology, researchers have begun to incorporate passive mechanical compliance into the design of legged robots, often by adding spring elements in series with the robot’s actuators. First introduced by the MIT Leg Laboratory, series elastic actuators (SEAs) have been shown to improve the fidelity and stability of closed-loop force controllers while simultaneously increasing shock tolerance. The chapter shows an example SEA utilized in the design of THOR, a compliant humanoid robot developed at Virginia Tech. Despite new advancements, several challenges remain before humanoids can be fielded in real-world applications that require a high degree of mobility. Model-based control approaches could greatly benefit from techniques found in the robust and adaptive control literature. The field is also interested in moving towards more efficient, human-like locomotion using biologically-inspired control strategies.

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Bar-Cohen, Yoseph. "EAP Actuators for Biomimetic Technologies with Humanlike Robots as one of the Ultimate Challenges." Advances in Science and Technology 61 (September 2008): 1–7. http://dx.doi.org/10.4028/www.scientific.net/ast.61.1.

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Since the Stone Age, people have tried to reproduce the human appearance, functions, and intelligence using art and technology. Any aspect that represents our physical and intellectual being has been a subject of copying, mimicking and inspiration. Recent surges in technology advances led to the emergence of increasingly more realistic humanlike robots and simulations. Making such robots is part of the field of biologically inspired technologies - also known as biomimetics - and it involves developing engineered systems that exhibit the appearance and behavior of biological systems. Robots with selectable characteristics and personality that are customized to our needs and with self-learning capability may become our household appliance or even companion and they may be used to perform hard to do and complex tasks. In enabling this technology such elements as artificial intelligence, muscles, vision, skin and others are increasingly improved. In this paper, making humanlike robots will be described with focus on the use of artificial muscles as the enabling technology and the related challenges.

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Parrott, Christopher, Tony J. Dodd, Joby Boxall, and Kirill Horoshenkov. "Simulation of the behavior of biologically-inspired swarm robots for the autonomous inspection of buried pipes." Tunnelling and Underground Space Technology 101 (July 2020): 103356. http://dx.doi.org/10.1016/j.tust.2020.103356.

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Journal articles on the topic 'Biologically-inspired robots'

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