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Journal articles on the topic 'Robotic terrain perception'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Shi, Wenlei, Zerui Li, Wenjun Lv, Yuping Wu, Ji Chang, and Xiaochuan Li. "Laplacian Support Vector Machine for Vibration-Based Robotic Terrain Classification." Electronics 9, no. 3 (2020): 513. http://dx.doi.org/10.3390/electronics9030513.

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The achievement of robot autonomy has environmental perception as a prerequisite. The hazards rendered from uneven, soft and slippery terrains, which are generally named non-geometric hazards, are another potential threat reducing the traversing efficient, and therefore receiving more and more attention from the robotics community. In the paper, the vibration-based terrain classification (VTC) is investigated by taking a very practical issue, i.e., lack of labels, into consideration. According to the intrinsic temporal correlation existing in the sampled terrain sequence, a modified Laplacian

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Kouame, Yann Olivier Akansie, C. Biradar Rajashekhar, Rajendra Karthik, and D. Devanagavi Geetha. "A terrain data collection sensor box towards a better analysis of terrains conditions." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 4 (2024): 4388–402. https://doi.org/10.11591/ijai.v13.i4.pp4388-4402.

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Autonomous mobile robots are increasingly used across various applications, relying on multiple sensors for environmental awareness and efficient task execution. Given the unpredictability of human environments, versatility is crucial for these robots. Their performance is largely determined by how they perceive their surroundings. This paper introduces a machine learning (ML) approach focusing on land conditions to enhance a robot’s locomotion. The authors propose a method to classify terrains for data collection, involving the design of an apparatus to gather field data. This design is

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Weisbin, C., and D. Perillard. "R & D Profile Jet Propulsion Laboratory Robotic Facilities and Associated Research." Robotica 9, no. 1 (1991): 7–21. http://dx.doi.org/10.1017/s0263574700015526.

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SUMMARYThis paper describes the robotics facilities and associated research program of the Jet Propulsion Laboratory, lead center in telerobotics for the United States National Aeronautics and Space Administration. Emphasis is placed on evolution from teleoperation to remote System automation. Research is described in manipulator modelling and control, real-time planning and monitoring, navigation in outdoor terrain, real-time sensing and perception, human-machine interface, and overall System architectures. Applications to NASA missions emphasize robotic spacecraft for solar System exploratio

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Moh, K. T., and Van Jiang. "A Miniature Robotic Gait Algorithm for Terrain-Adaptive Walking in Soft Ground Environments." International Academic Journal of Science and Engineering 12, no. 3 (2025): 43–49. https://doi.org/10.71086/iajse/v12i1/iajse1208.

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The ability of miniature robots to move efficiently across soft or deformable terrain remains a challenge, particularly when facing limits on power and control. To solve this problem, a robotic gait algorithm was developed to modify gait parameters in response to real-time feedback from the environment. The system combines a hierarchical command system with machine-learning terrain classification to move with precision and minimal power on unstable surfaces like sand, soil, and gravel. A visual perception component uses BoW representations and SVM to classify the terrain before contact, enabli

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Azcarate, Raul Fernando Garcia, Akhil Jayadeep, Aung Kyaw Zin, James Wei Shung Lee, M. A. Viraj J. Muthugala, and Mohan Rajesh Elara. "Adaptive Outdoor Cleaning Robot with Real-Time Terrain Perception and Fuzzy Control." Mathematics 13, no. 14 (2025): 2245. https://doi.org/10.3390/math13142245.

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Outdoor cleaning robots must operate reliably across diverse and unstructured surfaces, yet many existing systems lack the adaptability to handle terrain variability. This paper proposes a terrain-aware cleaning framework that dynamically adjusts robot behavior based on real-time surface classification and slope estimation. A 128-channel LiDAR sensor captures signal intensity images, which are processed by a ResNet-18 convolutional neural network to classify floor types as wood, smooth, or rough. Simultaneously, pitch angles from an onboard IMU detect terrain inclination. These inputs are tran

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Boboc, Răzvan Gabriel. "Robotic Applications in Skiing: A Systematic Review of Current Research and Challenges." Machines 13, no. 5 (2025): 397. https://doi.org/10.3390/machines13050397.

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This paper provides a comprehensive review of the current state of research on robotic technologies in sports, with a specific emphasis on skiing. Using a systematic review methodology, I conducted an extensive search for relevant academic articles and conference papers across several databases, including Scopus, Web of Science, and IEEE. A predefined set of keywords guided the search process, leading to an initial collection of 327 papers. After applying specific selection criteria, 24 studies were identified as most relevant to the topic. These selected works were analyzed in detail, coverin

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Park, Jae-Min, Sungchul Hong, and Hyu-Soung Shin. "Pilot Study of Low-Light Enhanced Terrain Mapping for Robotic Exploration in Lunar PSRs." Remote Sensing 15, no. 13 (2023): 3412. http://dx.doi.org/10.3390/rs15133412.

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The recent discovery of water ice in the lunar polar shadowed regions (PSRs) has driven interest in robotic exploration, due to its potential utilization to generate water, oxygen, and hydrogen that would enable sustainable human exploration in the future. However, the absence of direct sunlight in the PSRs poses a significant challenge for the robotic operation to obtain clear images, consequently impacting crucial tasks such as obstacle avoidance, pathfinding, and scientific investigation. In this regard, this study proposes a visual simultaneous localization and mapping (SLAM)-based robotic

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Edlinger, R., and A. Nüchter. "TERRAIN PREDICTION WITH A LOW-COST LIDAR SENSOR FOR MOBILE ROBOTS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W1-2022 (December 8, 2022): 81–86. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w1-2022-81-2022.

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Abstract. Terrain modelling influences various aspects of mobile robot navigation. The ability to explore in rough terrain and to recognise ground conditions are essential to perform different activities efficiently, safely and satisfactorily. For this reason, intelligent vehicles and robotic systems need cognitive capabilities to understand the terrain and derive information from it. The information is mostly acquired and processed by very high resolution 3D-cameras and LiDAR sensors which provide full 360-degree environmental view to deliver accurate 3D data. The aim of this paper is to find

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Raj, Anil K., Peter D. Neuhaus, Adrien M. Moucheboeuf, Jerryll H. Noorden, and David V. Lecoutre. "Mina: A Sensorimotor Robotic Orthosis for Mobility Assistance." Journal of Robotics 2011 (2011): 1–8. http://dx.doi.org/10.1155/2011/284352.

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While most mobility options for persons with paraplegia or paraparesis employ wheeled solutions, significant adverse health, psychological, and social consequences result from wheelchair confinement. Modern robotic exoskeleton devices for gait assistance and rehabilitation, however, can support legged locomotion systems for those with lower extremity weakness or paralysis. The Florida Institute for Human and Machine Cognition (IHMC) has developed the Mina, a prototype sensorimotor robotic orthosis for mobility assistance that provides mobility capability for paraplegic and paraparetic users. T

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Griffin, Brent, and Jessy Grizzle. "Nonholonomic virtual constraints and gait optimization for robust walking control." International Journal of Robotics Research 36, no. 8 (2017): 895–922. http://dx.doi.org/10.1177/0278364917708249.

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A key challenge in robotic bipedal locomotion is the design of feedback controllers that function well in the presence of uncertainty, in both the robot and its environment. This paper addresses the design of feedback controllers and periodic gaits that function well in the presence of modest terrain variation, without over-reliance on perception and a priori knowledge of the environment. Model-based design methods are introduced and subsequently validated in simulation and experiment on MARLO, an underactuated three-dimensional bipedal robot that is of roughly human size and is equipped with

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Wu, Baoju, Xiaohui Wu, Nanmu Hui, and Xiaowei Han. "Trajectory Planning and Singularity Avoidance Algorithm for Robotic Arm Obstacle Avoidance Based on an Improved Fast Marching Tree." Applied Sciences 14, no. 8 (2024): 3241. http://dx.doi.org/10.3390/app14083241.

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The quest for efficient and safe trajectory planning in robotic manipulation poses significant challenges, particularly in complex obstacle environments where the risk of encountering singularities and obstacles is high. Addressing this critical issue, our study presents a novel enhancement of the Fast Marching Tree (FMT) algorithm, ingeniously designed to navigate the complex terrain of Cartesian space with an unprecedented level of finesse. At the heart of our approach lies a sophisticated two-stage path point sampling strategy, ingeniously coupled with a singularity avoidance mechanism that

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Sinha, Arnab, and Panagiotis Papadakis. "Mind the gap: detection and traversability analysis of terrain gaps using LIDAR for safe robot navigation." Robotica 31, no. 7 (2013): 1085–101. http://dx.doi.org/10.1017/s0263574713000349.

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SUMMARYSafe navigation of robotic vehicles is considered as a key pre-requisite of successful mission operations within highly adverse and unconstrained environments. While there has been extensive research in the perception of positive obstacles, little progress can be accredited to the field of negative obstacles. This paper hypostatizes an elaborative attempt to address the problem of negative obstacle detection and traversability analysis in the form of gaps by processing 3-dimensional range data. The domain of application concerns Urban Search and Rescue scenarios that reflect environment

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de Cubber, Geert, Haris Balta, and Claude Lietart. "Teodor: A Semi-Autonomous Search and Rescue and Demining Robot." Applied Mechanics and Materials 658 (October 2014): 599–605. http://dx.doi.org/10.4028/www.scientific.net/amm.658.599.

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In this paper, we present a ground robotic system which is developed to deal with rough outdoor conditions. The platform is to be used as an environmental monitoring robot for 2 main application areas: - Humanitarian demining: The vehicle is equipped with a specialized multi-channel metal detector array. An unmanned aerial system supports it for locating suspected locations of mines, which can then be confirmed by the ground vehicle. - Search and rescue: The vehicle is equipped with human victim detection sensors and a 3D camera enabling it to assess the traversability of the terrain in front

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Gholami, Amir, and Alejandro Ramirez-Serrano. "Terrain Traversability via Sensed Data for Robots Operating Inside Heterogeneous, Highly Unstructured Spaces." Sensors 25, no. 2 (2025): 439. https://doi.org/10.3390/s25020439.

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This paper presents a comprehensive approach to evaluating the ability of multi-legged robots to traverse confined and geometrically complex unstructured environments. The proposed approach utilizes advanced point cloud processing techniques integrating voxel-filtered cloud, boundary and mesh generation, and dynamic traversability analysis to enhance the robot’s terrain perception and navigation. The proposed framework was validated through rigorous simulation and experimental testing with humanoid robots, showcasing the potential of the proposed approach for use in applications/environments c

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Tranzatto, Marco, Mihir Dharmadhikari, Lukas Bernreiter, et al. "Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned." Field Robotics 4, no. 1 (2024): 249–312. http://dx.doi.org/10.55417/fr.2024009.

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This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with the vision to facilitate the novel technologies necessary to reliably explore diverse underground environments despite the grueling challenges they present for robotic autonomy. Due to their geometric complexity, degraded perceptual conditions combined with lack of GNSS support, austere navigation conditions, and denied communications, subterranean settings render autonomous operations particularly demanding. In res

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Arora, Anshu Saxena, and Amit Arora. "The Race Between Cognitive and Artificial Intelligence." International Journal of Intelligent Information Technologies 16, no. 1 (2020): 1–16. http://dx.doi.org/10.4018/ijiit.2020010101.

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Research on human-robot interaction (HRI) is growing; however, focus on the congruent socio-behavioral HRI research fields of social cognition, socio-behavioral intentions, and code of ethics is lacking. Humans possess an inherent ability of integrating perception, cognition, and action; while robots may have limitations as they may not recognize an object or a being, navigate a terrain, and/or comprehend written or verbal language and instructions. This HRI research focuses on issues and challenges for both humans and robots from social, behavioral, technical, and ethical perspectives. The hu

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Wijayathunga, Liyana, Alexander Rassau, and Douglas Chai. "Challengesand Solutions for Autonomous Ground Robot Scene Understanding and Navigation in Unstructured Outdoor Environments: A Review." Applied Sciences 13, no. 17 (2023): 9877. http://dx.doi.org/10.3390/app13179877.

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The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, robots have achieved relatively high levels of autonomy. In more unstructured environments, however, the development of fully autonomous mobile robots remains challenging due to the complexity of understanding these environments. Many autonomous mobile robots use classical, learning-based or hybrid approaches for navigation. More recent learning-based methods may replace the

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Бельченко, Ф. М., И. Л. Ермолов, Г. Н. Нагайцев, and П. П. Остриков. "Specifics of underwater images transmission in marine robotics." MORSKIE INTELLEKTUAL`NYE TEHNOLOGII)</msg> 3, no. 4(62) (2023): 62–67. http://dx.doi.org/10.37220/mit.2023.62.4.066.

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Телеуправляемые (дистанционно управляемые) роботы составляют значительную часть современного парка роботов и используются для разведки местности и контроля состояния важных объектов и инфраструктуры в подводной среде. Применение телеуправления с участием оператора связано с несовершенством современных автономных робототехнических комплексов, поскольку в определенных ситуациях необходимо быстро и точно принимать решения по управлению роботом. Человек в цепи управления подводным роботом является ключевым звеном. При этом он сильно ограничен техническими возможностями информационных средств, ему

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Lacroix, Simon, Anthony Mallet, David Bonnafous, et al. "Autonomous Rover Navigation on Unknown Terrains: Functions and Integration." International Journal of Robotics Research 21, no. 10-11 (2002): 917–42. http://dx.doi.org/10.1177/0278364902021010841.

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Autonomous long-range navigation in partially known planetary-like terrains is still an open challenge for robotics. Navigating hundreds of meters without any human intervention requires the robot to be able to build various representations of its environment, to plan and execute trajectories according to the kind of terrain traversed, to control its motions and to localize itself as it moves. All these activities have to be scheduled, triggered, controlled and interrupted according to the rover context. In this paper, we briefly review some functionalities that have been developed in our labo

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Li, Yadian. "Bioinspired Robotics: A Review of Four-Leg Movement, Sensor Integration, and Multimodal Learning." Applied and Computational Engineering 165, no. 1 (2025): 93–101. https://doi.org/10.54254/2755-2721/2025.ld24812.

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Bioinspired robotics, as a cutting-edge direction in the field of robotics, provides a unique path for innovation in robotics technology by drawing on the evolutionary achievements of biological systems. As a review paper, this article systematically categorizes the three core modules of quadrupedal motion, sensor integration, and multimodal learning and provides a detailed analysis of their biomimetic principles, technical implementation, and application scenarios. The quadrupedal movement endows robots with excellent terrain adaptability, sensor integration constructs an environmental percep

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Mansor, Zulkifli, Addie Irawan, and Mohammad Fadhil Abas. "Evolution, Design, and Future Trajectories on Bipedal Wheel-legged Robot: A Comprehensive Review." International Journal of Robotics and Control Systems 3, no. 4 (2023): 673–703. http://dx.doi.org/10.31763/ijrcs.v3i4.1107.

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This comprehensive review delves into the realm of bipedal wheel-legged robots, focusing on their design, control, and applications in assistive technology and disaster mitigation. Drawing insights from various fields such as robotics, computer science, and biomechanics, it offers a holistic understanding of these robots' stability, adaptability, and efficiency. The analysis encompasses optimization techniques, sensor integration, machine learning, and adaptive control methods, evaluating their impact on robot capabilities. Emphasizing the need for adaptable, terrain-aware control algorithms,

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Kalwa, Joerg, Daniel Tietjen, Marina Carreiro-Silva, et al. "The European Project MORPH: Distributed UUV Systems for Multimodal, 3D Underwater Surveys." Marine Technology Society Journal 50, no. 4 (2016): 26–41. http://dx.doi.org/10.4031/mtsj.50.4.10.

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AbstractThe MORPH project (FP 7, 2012‐2016) is aimed at developing efficient methods and tools to map the underwater environment in situations that are not easily addressed by current technology. Namely, the missions that are of interest are those that involve underwater surveying and marine habitat mapping of rugged terrain and structures with full 3D complexity, including vertical cliffs. Potential applications include the study of cold water coral reef communities, ecosystems from underwater canyons, pipeline and harbor monitoring, or the inspection of wind turbine foundations. The project

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Wei, Yuhai, Wu Wei, and Yangbiao Zhang. "EfferDeepNet: An Efficient Semantic Segmentation Method for Outdoor Terrain." Machines 11, no. 2 (2023): 256. http://dx.doi.org/10.3390/machines11020256.

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The recognition of terrain and outdoor complex environments based on vision sensors is a key technology in practical robotics applications, and forms the basis of autonomous navigation and motion planning. While traditional machine learning methods can be applied to outdoor terrain recognition, their recognition accuracy is low. In order to improve the accuracy of outdoor terrain recognition, methods based on deep learning are widely used. However, the network structure of deep learning methods is very complex, and the number of parameters is large, which cannot meet the actual operating requi

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Huang, Peichen, Peikui Huang, Zihong Wang, Xiao Wu, Jie Liu, and Lixue Zhu. "Deep-Learning-Based Trunk Perception with Depth Estimation and DWA for Robust Navigation of Robotics in Orchards." Agronomy 13, no. 4 (2023): 1084. http://dx.doi.org/10.3390/agronomy13041084.

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Agricultural robotics is a complex, challenging, and exciting research topic nowadays. However, orchard environments present harsh conditions for robotics operability, such as terrain irregularities, illumination, and inaccuracies in GPS signals. To overcome these challenges, reliable landmarks must be extracted from the environment. This study addresses the challenge of accurate, low-cost, and efficient landmark identification in orchards to enable robot row-following. First, deep learning, integrated with depth information, is used for real-time trunk detection and location. The in-house dat

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Li, Qimeng, Franco Cicirelli, Andrea Vinci, Antonio Guerrieri, Wen Qi, and Giancarlo Fortino. "Quadruped Robots: Bridging Mechanical Design, Control, and Applications." Robotics 14, no. 5 (2025): 57. https://doi.org/10.3390/robotics14050057.

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Quadruped robots have emerged as a prominent field of research due to their exceptional mobility and adaptability in complex terrains. This paper presents an overview of quadruped robots, encompassing their design principles, control mechanisms, perception systems, and applications across various industries. We review the historical evolution and technological milestones that have shaped quadruped robotics. To understand their impact on performance and functionality, key aspects of mechanical design are analyzed, including leg configurations, actuation systems, and material selection. Control

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Zech, Philipp, Simon Haller, Safoura Rezapour Lakani, Barry Ridge, Emre Ugur, and Justus Piater. "Computational models of affordance in robotics: a taxonomy and systematic classification." Adaptive Behavior 25, no. 5 (2017): 235–71. http://dx.doi.org/10.1177/1059712317726357.

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J. J. Gibson’s concept of affordance, one of the central pillars of ecological psychology, is a truly remarkable idea that provides a concise theory of animal perception predicated on environmental interaction. It is thus not surprising that this idea has also found its way into robotics research as one of the underlying theories for action perception. The success of the theory in this regard has meant that existing research is both abundant and diffuse by virtue of the pursuit of multiple different paths and techniques with the common goal of enabling robots to learn, perceive, and act upon a

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Zech, Philipp, Simon Haller, Lakani Safoura Rezapour, Barry Ridge, Emre Ugur, and Justus Piater. "Computational models of affordance in robotics: a taxonomy and systematic classification." Adaptive Behavior 25, no. 5 (2017): 235–71. https://doi.org/10.1177/1059712317726357.

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J. J. Gibson's concept of affordance, one of the central pillars of ecological psychology, is a truly remarkable idea that provides a concise theory of animal perception predicated on environmental interaction. It is thus not surprising that this idea has also found its way into robotics research as one of the underlying theories for action perception. The success of the theory in this regard has meant that existing research is both abundant and diffuse by virtue of the pursuit of multiple different paths and techniques with the common goal of enabling robots to learn, perceive, and act up

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Carter, Aja, and Sonia Roberts. "The deep time perspective: How insights from millennia of evolving and extinct animals can inform robot design decision making." IOP Conference Series: Materials Science and Engineering 1261, no. 1 (2022): 012022. http://dx.doi.org/10.1088/1757-899x/1261/1/012022.

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Abstract Animals on the visible scale have been experimenting with body form and function in enumerable enviroments for the last 540 million years. Almost all of the variation in the history of life is now gone, leaving only a tiny fraction of what is possible alive in modern animals. Recently biological and engineering techniques have made it possible to robustly answer questions only the fossil record can provide, such as the history and original functions of certain behaviors. Robotics has already begun to champion inspiration from biology, but only from the small variation seen in extant t

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Quaglia, Giuseppe, Carmen Visconte, Leonardo Sabatino Scimmi, Matteo Melchiorre, Paride Cavallone, and Stefano Pastorelli. "Design of a UGV Powered by Solar Energy for Precision Agriculture." Robotics 9, no. 1 (2020): 13. http://dx.doi.org/10.3390/robotics9010013.

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In this paper, a novel UGV (unmanned ground vehicle) for precision agriculture, named “Agri.q,” is presented. The Agri.q has a multiple degrees of freedom positioning mechanism and it is equipped with a robotic arm and vision sensors, which allow to challenge irregular terrains and to perform precision field operations with perception. In particular, the integration of a 7 DOFs (degrees of freedom) manipulator and a mobile frame results in a reconfigurable workspace, which opens to samples collection and inspection in non-structured environments. Moreover, Agri.q mounts an orientable landing p

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Dai, Yanyan, DeokGyu Kim, and KiDong Lee. "An Advanced Approach to Object Detection and Tracking in Robotics and Autonomous Vehicles Using YOLOv8 and LiDAR Data Fusion." Electronics 13, no. 12 (2024): 2250. http://dx.doi.org/10.3390/electronics13122250.

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Accurately and reliably perceiving the environment is a major challenge in autonomous driving and robotics research. Traditional vision-based methods often suffer from varying lighting conditions, occlusions, and complex environments. This paper addresses these challenges by combining a deep learning-based object detection algorithm, YOLOv8, with LiDAR data fusion technology. The principle of this combination is to merge the advantages of these technologies: YOLOv8 excels in real-time object detection and classification through RGB images, while LiDAR provides accurate distance measurement and

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Ehrlich-Sommer, Florian, Bernhard Hörl, Christoph Gollob, Arne Nothdurft, Karl Stampfer, and Andreas Holzinger. "Robot usability in the wild: bridging accessibility gaps for diverse user groups in complex forestry operations." Universal Access in the Information Society, June 13, 2025. https://doi.org/10.1007/s10209-025-01234-2.

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Abstract This study evaluated the usability and effectiveness of robotic platforms working together with foresters in the wild on forest inventory tasks using LiDAR scanning. Emphasis was on the Universal Access principle, ensuring that robotic solutions are not only effective but also environmentally responsible and accessible for diverse users. Three robotic platforms were tested: Boston Dynamics Spot, AgileX Scout, and Bunker Mini. Spot’s quadrupedal locomotion struggled in dense undergrowth, leading to frequent mobility failures and a System Usability Scale (SUS) score of 78 ± 10. Its shor

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Jia, Lixin, Lihang Feng, Jiantao Shi, Dong Wang, Guangming Zhang, and Chun-YI Su. "An improved robotic arm constant force control method for forward terrain sensing system on planetary rovers." International Journal of Advanced Robotic Systems 21, no. 6 (2024). https://doi.org/10.1177/17298806241305883.

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The traversability of the terrain ahead of planetary rovers significantly impacts the success of their extraterrestrial exploration missions. Accurate perception of the terrain force through a forward wheel-on-limb detection system can provide crucial data for assessing the traversability of the terrain ahead. Existing constant force control methods, largely based on static terra mechanics models, struggle to meet the operational needs of planetary rovers in unknown environments. To address this issue, this paper proposes an improved adaptive impedance control method for robotic arms in unknow

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Arm, Philip, Gabriel Waibel, Jan Preisig, et al. "Scientific exploration of challenging planetary analog environments with a team of legged robots." Science Robotics 8, no. 80 (2023). http://dx.doi.org/10.1126/scirobotics.ade9548.

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The interest in exploring planetary bodies for scientific investigation and in situ resource utilization is ever-rising. Yet, many sites of interest are inaccessible to state-of-the-art planetary exploration robots because of the robots’ inability to traverse steep slopes, unstructured terrain, and loose soil. In addition, current single-robot approaches only allow a limited exploration speed and a single set of skills. Here, we present a team of legged robots with complementary skills for exploration missions in challenging planetary analog environments. We equipped the robots with an efficie

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Polzin, Max, Qinghua Guan, and Josie Hughes. "Robotic locomotion through active and passive morphological adaptation in extreme outdoor environments." Science Robotics 10, no. 99 (2025). https://doi.org/10.1126/scirobotics.adp6419.

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Robotic locomotion has shown substantial advancements, yet robots still lack the versatility and agility shown by animals navigating complex terrains. This limits their applicability in complex environments where they could be highly beneficial. Unlike existing robots that rely on intricate perception systems to construct models of both themselves and their surroundings, a more bioinspired approach leverages reconfiguration to adapt a robot’s morphology to its environment. Although interest in such multimodal, terrain-adaptive robots is increasing, their capacity for morphological reconfigurat

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Jia, Lixin, Mujia Shi, Jiantao Shi, et al. "Design and calibration of a novel multiaxis sensor for measuring the wheel–terrain interaction forces of robotic vehicles." Sensor Review, January 6, 2025. https://doi.org/10.1108/sr-10-2024-0849.

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Purpose This paper aims to propose a novel wheel-based multiaxis force sensor designed to detect the interaction forces and moments between the planetary rover’s wheel and the terrain, thereby assisting the rover in environmental perception. Design/methodology/approach The authors’ design approach encompasses the mechanical structure design, decoupling methods and component integration techniques, effectively incorporating multiaxis sensors into the forward-sensing wheel. This enables high-precision and high-reliability detection of wheel–terrain interaction forces and torques. Findings The de

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Cruz Ulloa, Christyan, Jaime Del Cerro, and Antonio Barrientos. "Perception sensor integration for improved environmental reconstruction in quadruped robotics." Jornadas de Automática, no. 45 (July 24, 2024). http://dx.doi.org/10.17979/ja-cea.2024.45.10830.

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Perception systems are fundamental in outdoor robotics, as their correct functionality is essential for tasks such as terrain identification, localization, navigation, and analysis of objects of interest. This is particularly relevant in search and rescue (SAR) robotics, where one current research focuses on the mobility and traversal of unstructured terrains (commonly resulting from natural disasters or attacks) using quadruped robots. 3D sensory systems, such as those based on 360-degree LiDAR, tend to create dead zones within a considerable radius relative to their placement (typically on t

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Miki, Takahiro, Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen, Vladlen Koltun, and Marco Hutter. "Learning robust perceptive locomotion for quadrupedal robots in the wild." Science Robotics 7, no. 62 (2022). http://dx.doi.org/10.1126/scirobotics.abk2822.

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Legged robots that can operate autonomously in remote and hazardous environments will greatly increase opportunities for exploration into underexplored areas. Exteroceptive perception is crucial for fast and energy-efficient locomotion: Perceiving the terrain before making contact with it enables planning and adaptation of the gait ahead of time to maintain speed and stability. However, using exteroceptive perception robustly for locomotion has remained a grand challenge in robotics. Snow, vegetation, and water visually appear as obstacles on which the robot cannot step or are missing altogeth

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Segars, Heidi, Anne Collins McLaughlin, Ericka Rovira, and Susan Mohammed. "The Influence of Operator Trust on Human-Robot Interaction Within Teams." Proceedings of the Human Factors and Ergonomics Society Annual Meeting, August 10, 2024. http://dx.doi.org/10.1177/10711813241260296.

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Utilizing advanced machinery in team environments often necessitates reliance on a leader, or “operator,” who is in charge of interfacing with technology directly on the team’s behalf. This is particularly evident in modern military missions, where teams depend on operators of robotic machinery to safely navigate dangerous tasks or hazardous terrain. The present work is part of a larger study on integrating a semi-autonomous quadruped robot into military training exercises. This analysis focused on how trust in an operator controlling Spot influenced different aspects of human-robot interactio

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E. Carvalho, Afonso, David Portugal, and Paulo Peixoto. "On terrain traversability analysis in unstructured environments: recent advances in forest applications." Intelligent Service Robotics, March 7, 2025. https://doi.org/10.1007/s11370-025-00591-4.

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Abstract In the field of mobile robotics and autonomous systems, the ability to navigate in unstructured environments is a major challenge. Unpredictable landscapes consisting of irregular and possibly unconsolidated terrain, especially in natural environments such as forests, require comprehensive analysis and innovative solutions for robot perception and control. This article provides an introduction to the field of traversability analysis, with a particular focus on recent advances tailored to forest environments. It presents both the classical and earlier techniques as well as current stat

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Liu, Kaishu, Jijun Gu, Xiaoyong He, and Long Zhang. "Optimization Algorithms for Dynamic Environmental Sensing and Motion Planning of Quadruped Robots in Complex Environments on Unmanned Offshore Platforms." Measurement Science and Technology, November 7, 2024. http://dx.doi.org/10.1088/1361-6501/ad8fc2.

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Abstract With the development of reduced-manning and unattended offshore oil and gas fields, quadruped robots have become essential tools for monitoring unattended offshore oil platforms and reducing operational costs. However, the complexity of these platforms makes real-time generation of quadruped robot motion based on environmental information a critical issue. We propose a comprehensive perception, planning, and control pipeline to optimize the robot's motion in real-time. To enhance environmental perception, we introduce an unsupervised learning clustering algorithm. Addressing the numer

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Rico, Francisco Martín, José Miguel Guerrero Hernández, Rodrigo Pérez‐Rodríguez, Juan Diego Peña‐Narvaez, and Alberto García Gómez‐Jacinto. "Open source robot localization for nonplanar environments." Journal of Field Robotics, May 7, 2024. http://dx.doi.org/10.1002/rob.22353.

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AbstractThe operational environments in which a mobile robot executes its missions often exhibit nonflat terrain characteristics, encompassing outdoor and indoor settings featuring ramps and slopes. In such scenarios, the conventional methodologies employed for localization encounter novel challenges and limitations. This study delineates a localization framework incorporating ground elevation and incline considerations, deviating from traditional two‐dimensional localization paradigms that may falter in such contexts. In our proposed approach, the map encompasses elevation and spatial occupan

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Gerdes, Levin, Tim Wiese, Raúl Castilla Arquillo, et al. "BASEPROD: The Bardenas Semi-Desert Planetary Rover Dataset." Scientific Data 11, no. 1 (2024). http://dx.doi.org/10.1038/s41597-024-03881-1.

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AbstractDataset acquisitions devised specifically for robotic planetary exploration are key for the advancement, evaluation, and validation of novel perception, localization, and navigation methods in representative environments. Originating in the Bardenas semi-desert in July 2023, the data presented in this Data Descriptor is primarily aimed at Martian exploration and contains relevant rover sensor data from approximately 1.7km of traverses, a high-resolution 3D map of the test area, laser-induced breakdown spectroscopy recordings of rock samples along the rover path, as well as local weathe

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Budiyono, Agus, Bismo Jelantik Joyodiharjo, and Ary Setijadi Prihatmanto. "Bio-Inspiration in Underwater Robotics: A State-of-the-Art Review." January 19, 2024. https://doi.org/10.5281/zenodo.13920261.

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Underwater robotics has witnessed significant advancements through the integration of bio-inspiration, leveraging nature's design principles to enhance the capabilities and performance of underwater robots. This paper presents a comprehensive state-of-the-art review of bio-inspiration in underwater robotics, exploring the diverse range of bio-inspired approaches and their applications in this field. The review begins by introducing the concept of bio-inspiration and its relevance to underwater robotics, highlighting the benefits of mimicking nature's solutions in terms of efficiency, adaptabil

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Pietrantoni, Luca, Marco Favilla, Federico Fraboni, et al. "Integrating collaborative robots in manufacturing, logistics, and agriculture: Expert perspectives on technical, safety, and human factors." Frontiers in Robotics and AI 11 (December 2, 2024). https://doi.org/10.3389/frobt.2024.1342130.

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This study investigates the implementation of collaborative robots across three distinct industrial sectors: vehicle assembly, warehouse logistics, and agricultural operations. Through the SESTOSENSO project, an EU-funded initiative, we examined expert perspectives on human-robot collaboration using a mixed-methods approach. Data were collected from 31 technical experts across nine European countries through an online questionnaire combining qualitative assessments of specific use cases and quantitative measures of attitudes, trust, and safety perceptions. Expert opinions across the use cases

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Quaglia, Giuseppe, Carmen Visconte, Leonardo Sabatino Scimmi, Matteo Melchiorre, Paride Cavallone, and Stefano Pastorelli. "Design of a UGV Powered by Solar Energy for Precision Agriculture." March 17, 2020. https://doi.org/10.3390/robotics9010013.

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In this paper, a novel UGV (unmanned ground vehicle) for precision agriculture, named "Agri.q," is presented. The Agri.q has a multiple degrees of freedom positioning mechanism and it is equipped with a robotic arm and vision sensors, which allow to challenge irregular terrains and to perform precision field operations with perception. In particular, the integration of a 7 DOFs (degrees of freedom) manipulator and a mobile frame results in a reconfigurable workspace, which opens to samples collection and inspection in non-structured environments. Moreover, Agri.q mounts an orientable landing p

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Kurbis, Andrew Garrett, Dmytro Kuzmenko, Bogdan Ivanyuk-Skulskiy, Alex Mihailidis, and Brokoslaw Laschowski. "StairNet: visual recognition of stairs for human–robot locomotion." BioMedical Engineering OnLine 23, no. 1 (2024). http://dx.doi.org/10.1186/s12938-024-01216-0.

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AbstractHuman–robot walking with prosthetic legs and exoskeletons, especially over complex terrains, such as stairs, remains a significant challenge. Egocentric vision has the unique potential to detect the walking environment prior to physical interactions, which can improve transitions to and from stairs. This motivated us to develop the StairNet initiative to support the development of new deep learning models for visual perception of real-world stair environments. In this study, we present a comprehensive overview of the StairNet initiative and key research to date. First, we summarize the

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Capiola, August, Izz aldin Hamdan, Joseph B. Lyons, Michael Lewis, Gene M. Alarcon, and Katia Sycara. "The Effect of Asset Degradation on Trust in Swarms: A Reexamination of System-Wide Trust in Human-Swarm Interaction." Human Factors: The Journal of the Human Factors and Ergonomics Society, December 13, 2022, 001872082211452. http://dx.doi.org/10.1177/00187208221145261.

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Objective The effects of asset degradation on trust in human-swarm interaction were investigated through the lens of system-wide trust theory. Background Researchers have begun investigating contextual features that shape human interactions with robotic swarms—systems comprising assets that coordinate behavior based on their nearest neighbors. Recent work has begun investigating how human trust toward swarms is affected by asset degradation through the lens of system-wide trust theory, but these studies have been marked by several limitations. Method In an online study, the current work manipu

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De Boisboissel, G. "Արհեստական բանականություն. կիրառման նոր ձևերը և ազդեցությունը զորքերի մարտական կառավարման վրա / Artificial intelligence: new uses and impacts on military command and control". Հայկական բանակ / Armenian Army, 2024, 36–70. https://doi.org/10.61760/18290108-ehb24.2-36.

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General information and background on AI 1.1 The three battlefield revolutions The digitisation of the battlefield is a major revolution in combat, which needs to be assessed on a long-term scale as it will profoundly change military operating methods. First of all, it will mean that all the equipment deployed in the field will be interconnected with a tactical bubble that enables secure data exchanges to reduce the fog of war. What is already true for many armoured vehicles* will be true in the future for the dismounted soldier himself, who will be carrying advanced technologies. Processing t

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Li, Yiqun, Siyuan Qiao, Haoluo Shao, and Zhouping Yin. "Geometric Adaptive Neural Controller and Optical Flow‐Based Invariant Extended Kalman Filter for Mars Quadrotor Under Disturbance." Journal of Field Robotics, February 11, 2025. https://doi.org/10.1002/rob.22523.

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ABSTRACTWith the continuous progress of deep space robotics technology and the deepening of human understanding of the Martian surface environment, the rotorcraft is expected to overcome the limitations of Mars orbiters and rovers in terms of exploration accuracy, range, and flexibility. Rotorcraft are poised to become essential vehicles for future deep space exploration missions. In this paper, an invariant extended Kalman filter (IEKF) and geometric adaptive neural controllers (GANC) are introduced for the state estimation and trajectory tracking of the Mars quadrotor. The IEKF fuses the IMU

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Monger, Simone. "Motion Classification of Objects using Accelerometer and Gyroscope Readings." Inquiry@Queen's Undergraduate Research Conference Proceedings 18, no. 2 (2024). http://dx.doi.org/10.24908/iqurcp18055.

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It can be challenging to properly analyze data from moving objects when there is limited information about the conditions under which the data was collected. The focus of this research is to use accelerometer and gyroscope data as the input to machine learning models to accurately classify data points based on the movement of the object within its environment. Three machine learning models were implemented and tested: a Hidden Markov Model (HMM), a Random Forest Model (RF), and a Multilayer Perceptron Model (MLP). The majority of the data collected via a simulated environment in Gazebo was use

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