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Journal articles on the topic 'Local motion planner'

Author: Grafiati

Published: 29 June 2021

Last updated: 29 July 2025

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1

Karakaya, Suat, and Hasan Ocak. "A Novel Local Motion Planner: Navibug." Journal of Intelligent & Robotic Systems 100, no. 3-4 (2020): 987–1003. http://dx.doi.org/10.1007/s10846-020-01239-4.

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2

Yoshida, Eiichi, Satoshi Murata, Akiya Kamimura, Kohji Tomita, Haruhisa Kurokawa, and Shigeru Kokaji. "Motion Generation for a Modular Robot." Journal of Robotics and Mechatronics 14, no. 2 (2002): 177–85. http://dx.doi.org/10.20965/jrm.2002.p0177.

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We discuss motion generation of a homogeneous modular robot called a Modular Transformer (M-TRAN). Modules are designed to be self-reconfigurable so a collection of modules can transform itself into a robotic structure. The motion generation of the self-reconfigurable robot presents a computationally difficult problem due to the many combinatorial possibilities for the module configuration, even though the module itself is simple, with 2 degrees of freedom. We describe a motion generation for a class of multimodule structures based on a motion planner and a motion scheduler. The motion planner

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3

Chiurazzi, Marcello, Joan Ortega Alcaide, Alessandro Diodato, Arianna Menciassi, and Gastone Ciuti. "Spherical Wrist Manipulator Local Planner for Redundant Tasks in Collaborative Environments." Sensors 23, no. 2 (2023): 677. http://dx.doi.org/10.3390/s23020677.

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Standard industrial robotic manipulators use well-established high performing technologies. However, such manipulators do not guarantee a safe Human–Robot Interaction (HRI), limiting their usage in industrial and medical applications. This paper proposes a novel local path planner for spherical wrist manipulators to control the execution of tasks where the manipulator number of joints is redundant. Such redundancy is used to optimize robot motion and dexterity. We present an intuitive parametrization of the end-effector (EE) angular motion, which decouples the rotation of the third joint of th

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Hoshino, Satoshi, and Kenichiro Uchida. "Interactive Motion Planning for Mobile Robot Navigation in Dynamic Environments." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 4 (2017): 667–74. http://dx.doi.org/10.20965/jaciii.2017.p0667.

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In dynamic environments, taking static and moving obstacles into consideration in motion planning for mobile robot navigation is a technical issue. In this paper, we use a single mobile robot, for which humans are moving obstacles. Since moving humans sometimes get in the way of the robot, it must avoid collisions with them. Furthermore, if a part of the environment is crowded with humans, it is better for the robot to detour around the congested area. For this navigational challenge, we focus on the interaction between humans and the robot, so this paper proposes a motion planner for successf

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Garrido, S., L. Moreno, D. Blanco, and M. L. Munoz. "Sensor-based global planning for mobile robot navigation." Robotica 25, no. 2 (2007): 189–99. http://dx.doi.org/10.1017/s0263574707003384.

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SUMMARYThe proposed algorithm integrates in a single planner the global motion planning and local obstacle avoidance capabilities. It efficiently guides the robot in a dynamic environment. This eliminates some of the traditional problems of planned architectures (model-plan-act scheme) while obtaining many of the qualities of behavior-based architectures. The computational efficiency of the method allows the planner to operate at high-rate sensor frequencies. This avoids the need for using both a collision-avoidance algorithm and a global motion planner for navigation in a cluttered environmen

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Vass, Gábor, Béla Lantos, and Shahram Payandeh. "Object Reconfiguration with Dextrous Robot Agents." Journal of Advanced Computational Intelligence and Intelligent Informatics 10, no. 2 (2006): 234–40. http://dx.doi.org/10.20965/jaciii.2006.p0234.

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This paper addresses an object manipulation planning algorithm for dextrous robot systems consisting a multifingered hand and a robotic manipulator. A method has been developed for object reconfiguration design. The result is a new algorithm using artificial intelligence based on simulated annealing and A* search. The upper level of the manipulation system, the global planner generates the motion of the object. The lower level, the local planner deals with the motion of the agents relative to the object and the design of the contact forces. The local planner is based on simulated annealing, th

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Lin, Chien-Chou, Kun-Cheng Chen, and Wei-Ju Chuang. "Motion Planning Using a Memetic Evolution Algorithm for Swarm Robots." International Journal of Advanced Robotic Systems 9, no. 1 (2012): 19. http://dx.doi.org/10.5772/45669.

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A hierarchical memetic algorithm (MA) is proposed for the path planning and formation control of swarm robots. The proposed algorithm consists of a global path planner (GPP) and a local motion planner (LMP). The GPP plans a trajectory within the Voronoi diagram (VD) of the free space. An MA with a non-random initial population plans a series of configurations along the path given by the former stage. The MA locally adjusts the robot positions to search for better fitness along the gradient direction of the distance between the swarm robots and the intermediate goals (IGs). Once the optimal con

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8

Du, Hang, Ming You, and Xinyi Zhao. "Globally Guided Deep V-Network-Based Motion Planning Algorithm for Fixed-Wing Unmanned Aerial Vehicles." Sensors 24, no. 12 (2024): 3984. http://dx.doi.org/10.3390/s24123984.

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Fixed-wing UAVs have shown great potential in both military and civilian applications. However, achieving safe and collision-free flight in complex obstacle environments is still a challenging problem. This paper proposed a hierarchical two-layer fixed-wing UAV motion planning algorithm based on a global planner and a local reinforcement learning (RL) planner in the presence of static obstacles and other UAVs. Considering the kinematic constraints, a global planner is designed to provide reference guidance for ego-UAV with respect to static obstacles. On this basis, a local RL planner is desig

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Tang, Xin, Boyuan Li, and Haiping Du. "A Study on Dynamic Motion Planning for Autonomous Vehicles Based on Nonlinear Vehicle Model." Sensors 23, no. 1 (2022): 443. http://dx.doi.org/10.3390/s23010443.

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Autonomous driving technology, especially motion planning and the trajectory tracking method, is the foundation of an intelligent interconnected vehicle, which needs to be improved urgently. Currently, research on path planning methods has improved, but few of the current studies consider the vehicle’s nonlinear characteristics in the reference model, due to the heavy computational effort. At present, most of the algorithms are designed by a linear vehicle model in order to achieve the real-time performance at the cost of lost accuracy. To achieve a better performance, the dynamics and kinemat

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Tian, Yuan, and Feng Gao. "Efficient motion generation for a six-legged robot walking on irregular terrain via integrated foothold selection and optimization-based whole-body planning." Robotica 36, no. 3 (2017): 333–52. http://dx.doi.org/10.1017/s0263574717000418.

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SUMMARYIn this paper, an efficient motion planning method is proposed for a six-legged robot walking on irregular terrain. The method provides the robot with fast-generated free-gait motions to traverse the terrain with medium irregularities. We first of all introduce our six-legged robot with legs in parallel mechanism. After that, we decompose the motion planning problem into two main steps: first is the foothold selection based on a local footstep cost map, in which both terrain features and the robot mobility are considered; second is a whole-body configuration planner which casts the prob

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McConachie, Dale, Andrew Dobson, Mengyao Ruan, and Dmitry Berenson. "Manipulating deformable objects by interleaving prediction, planning, and control." International Journal of Robotics Research 39, no. 8 (2020): 957–82. http://dx.doi.org/10.1177/0278364920918299.

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We present a framework for deformable object manipulation that interleaves planning and control, enabling complex manipulation tasks without relying on high-fidelity modeling or simulation. The key question we address is when should we use planning and when should we use control to achieve the task? Planners are designed to find paths through complex configuration spaces, but for highly underactuated systems, such as deformable objects, achieving a specific configuration is very difficult even with high-fidelity models. Conversely, controllers can be designed to achieve specific configurations

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Bautista-Camino, Pedro, Alejandro I. Barranco-Gutiérrez, Ilse Cervantes, Martin Rodríguez-Licea, Juan Prado-Olivarez, and Francisco J. Pérez-Pinal. "Local Path Planning for Autonomous Vehicles Based on the Natural Behavior of the Biological Action-Perception Motion." Energies 15, no. 5 (2022): 1769. http://dx.doi.org/10.3390/en15051769.

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Local path planning is a key task for the motion planners of autonomous vehicles since it commands the vehicle across its environment while avoiding any obstacles. To perform this task, the local path planner generates a trajectory and a velocity profile, which are then sent to the vehicle’s actuators. This paper proposes a new local path planner for autonomous vehicles based on the Attractor Dynamic Approach (ADA), which was inspired by the behavior of movement of living beings, along with an algorithm that takes into account four acceleration policies, the ST dynamic vehicle model, and sever

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Hong, Sun-Gi, and Ju-Jang Lee. "A local motion planner for car-like robots in a cluttered environment." Artificial Life and Robotics 1, no. 1 (1997): 39–42. http://dx.doi.org/10.1007/bf02471111.

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Looi, Chen Zheng, and Danny Wee Kiat Ng. "A Study on the Effect of Parameters for ROS Motion Planer and Navigation System for Indoor Robot." International Journal of Electrical and Computer Engineering Research 1, no. 1 (2021): 29–36. http://dx.doi.org/10.53375/ijecer.2021.21.

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In the past decades, the service robot industry had risen rapidly. The office assistant robot is one type of service robot used to assist officers in an office environment. For the robot to navigate autonomously in the office, navigation algorithms and motion planners were implemented on these robots. Robot Operating System (ROS) is one of the common platforms to develop these robots. The parameters applied to the motion planners will affect the performance of the Robot. In this study, the global planners, A* and Dijkstra algorithm and local planners, Dynamic Window Approach (DWA) and Time Ela

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15

Zhong, Jingze, Mengjie Zhang, Zonghai Chen, and Jikai Wang. "Dynamic Obstacle Avoidance for Mobile Robots Based on 2D Differential Euclidean Signed Distance Field Maps in Park Environment." World Electric Vehicle Journal 15, no. 7 (2024): 320. http://dx.doi.org/10.3390/wevj15070320.

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In this paper, a novel and complete navigation system is proposed for mobile robots in a park environment, which can achieve safe and stable navigation as well as robust dynamic obstacle avoidance. The navigation system includes a global planning layer and a local planning layer. The global planner plans a series of way-points using the A* algorithm based on an offline stored occupancy grid map and sends them to the local planner. The local planner incorporates a dynamic obstacle avoidance mechanism. In contrast to existing dynamic obstacle avoidance algorithms based on trajectory tracking, we

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16

Xu, Jing, Jinghui Qiao, Xu Han, Yu He, Hongkun Tian, and Zhe Wei. "A Random Sampling-Based Method via Gaussian Process for Motion Planning in Dynamic Environments." Applied Sciences 12, no. 24 (2022): 12646. http://dx.doi.org/10.3390/app122412646.

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Motion planning is widely applied to industrial robots, medical robots, bionic robots, and smart vehicles. Most work environments of robots are not static, which leads to difficulties for robot motion planning. We present a dynamic Gaussian local planner (DGLP) method to solve motion planning problems in dynamic environments. In a dynamic environment, dynamic obstacles sometimes make part of the global path invalid, so the local invalid path needs to be local re-planned online. Compared with the node sampling-based methods building large-scale random trees or roadmaps, the Gaussian random path

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Andreasson, Henrik, Jonas Larsson, and Stephanie Lowry. "A Local Planner for Accurate Positioning for a Multiple Steer-and-Drive Unit Vehicle Using Non-Linear Optimization." Sensors 22, no. 7 (2022): 2588. http://dx.doi.org/10.3390/s22072588.

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This paper presents a local planning approach that is targeted for pseudo-omnidirectional vehicles: that is, vehicles that can drive sideways and rotate on the spot. This local planner—MSDU–is based on optimal control and formulates a non-linear optimization problem formulation that exploits the omni-motion capabilities of the vehicle to drive the vehicle to the goal in a smooth and efficient manner while avoiding obstacles and singularities. MSDU is designed for a real platform for mobile manipulation where one key function is the capability to drive in narrow and confined areas. The real-wor

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Sayols, Narcís, Albert Hernansanz, Alessio Sozzi, et al. "Dynamic Global/Local multi-layer motion planner architecture for autonomous Cognitive Surgical Robots." Robotics and Autonomous Systems 180 (October 2024): 104758. http://dx.doi.org/10.1016/j.robot.2024.104758.

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Xu, Wang-bao, Jie Zhao, Xue-bo Chen, and Ying Zhang. "Artificial moment method using attractive points for the local path planning of a single robot in complicated dynamic environments." Robotica 31, no. 8 (2013): 1263–74. http://dx.doi.org/10.1017/s0263574713000477.

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SUMMARYA novel path planner is presented for the local path planning of a single robot (represented with R) in a complicated dynamic environment. Here a series of attractive points are computed based on attractive segments for guiding R to move along a shorter path. Each attractive segment is obtained by using the full environmental knowledge and will be used for several sampling times in general. A motion controller, which is designed based on artificial moments and a robot model that has a principal motion direction line(PMDline), makes R move closely to attractive points while away from obs

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Pan, Jia, Christian Lauterbach, and Dinesh Manocha. "g-Planner: Real-time Motion Planning and Global Navigation using GPUs." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (2010): 1245–51. http://dx.doi.org/10.1609/aaai.v24i1.7732.

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We present novel randomized algorithms for solving global motion planning problems that exploit the computational capabilities of many-core GPUs. Our approach uses thread and data parallelism to achieve high performance for all components of sample-based algorithms, including random sampling, nearest neighbor computation, local planning, collision queries and graph search. The approach can efficiently solve both the multi-query and single-query versions of the problem and obtain considerable speedups over prior CPU-based algorithms. We demonstrate the efficiency of our algorithms by applying t

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Chen, Hanlin, Xizhe Zang, Yubin Liu, Xuehe Zhang, and Jie Zhao. "A Hierarchical Motion Planning Method for Mobile Manipulator." Sensors 23, no. 15 (2023): 6952. http://dx.doi.org/10.3390/s23156952.

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This paper focuses on motion planning for mobile manipulators, which includes planning for both the mobile base and the manipulator. A hierarchical motion planner is proposed that allows the manipulator to change its configuration autonomously in real time as needed. The planner has two levels: global planning for the mobile base in two dimensions and local planning for both the mobile base and the manipulator in three dimensions. The planner first generates a path for the mobile base using an optimized A* algorithm. As the mobile base moves along the path with the manipulator configuration un

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Zeng, Junjie, Long Qin, Yue Hu, Quanjun Yin, and Cong Hu. "Integrating a Path Planner and an Adaptive Motion Controller for Navigation in Dynamic Environments." Applied Sciences 9, no. 7 (2019): 1384. http://dx.doi.org/10.3390/app9071384.

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Since an individual approach can hardly navigate robots through complex environments, we present a novel two-level hierarchical framework called JPS-IA3C (Jump Point Search improved Asynchronous Advantage Actor-Critic) in this paper for robot navigation in dynamic environments through continuous controlling signals. Its global planner JPS+ (P) is a variant of JPS (Jump Point Search), which efficiently computes an abstract path of neighboring jump points. These nodes, which are seen as subgoals, completely rid Deep Reinforcement Learning (DRL)-based controllers of notorious local minima. To sat

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Younes, Younes Al, and Martin Barczyk. "Optimal Motion Planning in GPS-Denied Environments Using Nonlinear Model Predictive Horizon." Sensors 21, no. 16 (2021): 5547. http://dx.doi.org/10.3390/s21165547.

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Navigating robotic systems autonomously through unknown, dynamic and GPS-denied environments is a challenging task. One requirement of this is a path planner which provides safe trajectories in real-world conditions such as nonlinear vehicle dynamics, real-time computation requirements, complex 3D environments, and moving obstacles. This paper presents a methodological motion planning approach which integrates a novel local path planning approach with a graph-based planner to enable an autonomous vehicle (here a drone) to navigate through GPS-denied subterranean environments. The local path pl

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Xiang, Ao, Chenzhang Gong, and Li Fan. "Map Representation and Navigation Planning for Legged Climbing UGVs in 3D Environments." Drones 8, no. 12 (2024): 768. https://doi.org/10.3390/drones8120768.

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Legged climbing unmanned ground vehicles (LC-UGVs) possess obstacle avoidance and wall transition capabilities, allowing them to move in 3D environments. Existing navigation methods for legged UGVs are only suitable for ground locomotion rather than 3D space. Although some wall transition methods have been proposed, they are specific to certain legged structures and have not been integrated into the navigation framework in full 3D environments. The planning of collision-free and accessible paths for legged climbing UGVs with any configuration in a 3D environment remains an open problem. This p

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Shvalb, Nir, Boaz Ben Moshe, and Oded Medina. "A real-time motion planning algorithm for a hyper-redundant set of mechanisms." Robotica 31, no. 8 (2013): 1327–35. http://dx.doi.org/10.1017/s0263574713000489.

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SUMMARYWe introduce a novel probabilistic algorithm (CPRM) for real-time motion planning in the configuration space${\EuScript C}$. Our algorithm differs from a probabilistic road map (PRM) algorithm in the motion between a pair of anchoring points (local planner) which takes place on the boundary of the obstacle subspace${\EuScript O}$. We define a varying potential fieldfon ∂${\EuScript O}$as a Morse function and follow$\vec{\nabla} f$. We then exemplify our algorithm on a redundant worm climbing robot withndegrees of freedom and compare our algorithm running results with those of the PRM.

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Ranganeni, Vinitha, Oren Salzman, and Maxim Likhachev. "Effective Footstep Planning for Humanoids Using Homotopy-Class Guidance." Proceedings of the International Conference on Automated Planning and Scheduling 28 (June 15, 2018): 500–508. http://dx.doi.org/10.1609/icaps.v28i1.13922.

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Planning the motion for humanoid robots is a computationally-complex task due to the high dimensionality of the system. Thus, a common approach is to first plan in the low-dimensional space induced by the robot’s feet—a task referred to as footstep planning. This low-dimensional plan is then used to guide the full motion of the robot. One approach that has proven successful in footstep planning is using search-based planners such as A* and its many variants. To do so, these search-based planners have to be endowed with effective heuristics to efficiently guide them through the search space. Ho

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HENTOUT, Abdelfetah, Abderraouf MAOUDJ, and Ahmed KOUIDER. "Shortest Path Planning and Efficient Fuzzy Logic Control of Mobile Robots in Indoor Static and Dynamic Environments." Romanian Journal of Information Science and Technology 2024, no. 1 (2024): 21–36. http://dx.doi.org/10.59277/romjist.2024.1.02.

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Efficient navigation in dynamic environments is a critical skill for of mobile robots, where obstacles can stochastically appear. This paper presents a complete navigation and control system that integrates effective path optimization and motion control capabilities for mobile robots evolving in indoor static and dynamic environments. This system consists primarily of two layers. In the Optimization Layer (Global planner), a Deterministic Constructive Algorithm (DCA) quickly generates the shortest path, as a sequence of nodes, to get to the goal position while avoiding the static obstacles. Th

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Park, Chonhyon, Jia Pan, and Dinesh Manocha. "High-DOF Robots in Dynamic Environments Using Incremental Trajectory Optimization." International Journal of Humanoid Robotics 11, no. 02 (2014): 1441001. http://dx.doi.org/10.1142/s0219843614410011.

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We present a novel optimization-based motion planning algorithm for high degree-of-freedom (DOF) robots in dynamic environments. Our approach decomposes the high-dimensional motion planning problem into a sequence of low-dimensional sub-problems. We compute collision-free and smooth paths using optimization-based planning and trajectory perturbation for each sub-problem. The overall algorithm does not require a priori knowledge about global motion or trajectories of dynamic obstacles. Rather, we compute a conservative local bound on the position or trajectory of each obstacle over a short time

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29

Quer, Stefano, and Luz Garcia. "Modules and Techniques for Motion Planning: An Industrial Perspective." Sensors 21, no. 2 (2021): 420. http://dx.doi.org/10.3390/s21020420.

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Research on autonomous cars has become one of the main research paths in the automotive industry, with many critical issues that remain to be explored while considering the overall methodology and its practical applicability. In this paper, we present an industrial experience in which we build a complete autonomous driving system, from the sensor units to the car control equipment, and we describe its adoption and testing phase on the field. We report how we organize data fusion and map manipulation to represent the required reality. We focus on the communication and synchronization issues bet

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Quer, Stefano, and Luz Garcia. "Modules and Techniques for Motion Planning: An Industrial Perspective." Sensors 21, no. 2 (2021): 420. http://dx.doi.org/10.3390/s21020420.

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Research on autonomous cars has become one of the main research paths in the automotive industry, with many critical issues that remain to be explored while considering the overall methodology and its practical applicability. In this paper, we present an industrial experience in which we build a complete autonomous driving system, from the sensor units to the car control equipment, and we describe its adoption and testing phase on the field. We report how we organize data fusion and map manipulation to represent the required reality. We focus on the communication and synchronization issues bet

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31

Wang, Daifeng, Wenjing Cao, and Atsuo Takanishi. "Dual-Quaternion-Based SLERP MPC Local Controller for Safe Self-Driving of Robotic Wheelchairs." Robotics 12, no. 6 (2023): 153. http://dx.doi.org/10.3390/robotics12060153.

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In this work, the motion control of a robotic wheelchair to achieve safe and intelligent movement in an unknown scenario is proposed. The primary objective is to develop a comprehensive framework for a robotic wheelchair that combines a global path planner and a model predictive control (MPC) local controller. The A* algorithm is employed to generate a global path. To ensure safe and directional motion for the wheelchair user, an MPC local controller is implemented taking into account the via points generated by an approach combined with dual quaternions and spherical linear interpolation (SLE

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Shigemura, Atsushi, Yuki Ishikawa, Jun Miura, and Junji Satake. "An RT Component for Simulating People Movement in Public Space and its Application to Robot Motion Planner Development." Journal of Robotics and Mechatronics 24, no. 1 (2012): 165–73. http://dx.doi.org/10.20965/jrm.2012.p0165.

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This paper describes a software module for simulating “people movement” in public space such as shopping centers and cafeterias. We decompose people movement into global and local, and make a model of each of them. Global movement corresponds to following a route from a current position to a destination. In local movement, a person moves toward the next subgoal while avoiding surrounding persons and obstacles. We also model behavior specific to a cafeteria, such as queuing and searching for unoccupied seats. We implement these simulation algorithms in a simulator RT component, that can be used

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Park, Chonhyon, Jia Pan, and Dinesh Manocha. "ITOMP: Incremental Trajectory Optimization for Real-Time Replanning in Dynamic Environments." Proceedings of the International Conference on Automated Planning and Scheduling 22 (May 14, 2012): 207–15. http://dx.doi.org/10.1609/icaps.v22i1.13513.

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We present a novel optimization-based algorithm for motion planning in dynamic environments. Our approach uses a stochastic trajectory optimization framework to avoid collisions and satisfy smoothness and dynamics constraints. Our algorithm does not require a priori knowledge about global motion or trajectories of dynamic obstacles. Rather, we compute a conservative local bound on the position or trajectory of each obstacle over a short time and use the bound to compute a collision-free trajectory for the robot in an incremental manner. Moreover, we interleave planning and execution of the rob

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Sun, Jiubo, Guoliang Liu, Guohui Tian, and Jianhua Zhang. "Smart Obstacle Avoidance Using a Danger Index for a Dynamic Environment." Applied Sciences 9, no. 8 (2019): 1589. http://dx.doi.org/10.3390/app9081589.

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The artificial potential field approach provides a simple and effective motion planner for robot navigation. However, the traditional artificial potential field approach in practice can have a local minimum problem, i.e., the attractive force from the target position is in the balance with the repulsive force from the obstacle, such that the robot cannot escape from this situation and reach the target. Moreover, the moving object detection and avoidance is still a challenging problem with the current artificial potential field method. In this paper, we present an improved version of the artifi

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ZHANG, Hongwen, Zhanxia ZHU, and Jianping YUAN. "Non-inverse kinematics of free-floating space robot based on motion planning of sampling." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, no. 5 (2021): 1005–11. http://dx.doi.org/10.1051/jnwpu/20203951005.

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Motion planning is one of the fundamental technologies for robots to achieve autonomy. Free-floating space robots composed manipulators and base satellite that do not actively control its position and attitude has nonholonomic characteristics, and there is a first-order differential relationship between its joint angle and the base attitude. In addition, the planning framework which first converts the goal end-effector pose to its corresponding target configuration, and then plan the trajectory from the initial configuration to the goal configuration still has the following problems: the goal

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Ahmed, Alaa, Turki Abdalla, and Ali Abed. "Path Planning of Mobile Robot Using Fuzzy-Potential Field Method." Iraqi Journal for Electrical and Electronic Engineering 11, no. 1 (2015): 32–41. http://dx.doi.org/10.37917/ijeee.11.1.4.

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This paper deals with the navigation of a mobile robot in unknown environment using artificial potential field method. The aim of this paper is to develop a complete method that allows the mobile robot to reach its goal while avoiding unknown obstacles on its path. An approach proposed is introduced in this paper based on combing the artificial potential field method with fuzzy logic controller to solve drawbacks of artificial potential field method such as local minima problems, make an effective motion planner and improve the quality of the trajectory of mobile robot.

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Yan, Haibo. "Vehicle Safety-Assisted Driving Technology Based on Computer Artificial Intelligence Environment." Computational Intelligence and Neuroscience 2022 (June 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/4390394.

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In this paper, we propose an assisted driving system implemented with a Jetson nano-high-performance embedded platform by using machine vision and deep learning technologies. The vehicle dynamics model is established under multiconditional assumptions, the path planner and path tracking controller are designed based on the model predictive control algorithm, and the local desired path is reasonably planned in combination with the behavioral decision system. The behavioral decision algorithm based on finite state machine reasonably transforms the driving state according to the environmental cha

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Wang, Rui, Kai Gao, Jingjin Yu, and Kostas Bekris. "Lazy Rearrangement Planning in Confined Spaces." Proceedings of the International Conference on Automated Planning and Scheduling 32 (June 13, 2022): 385–93. http://dx.doi.org/10.1609/icaps.v32i1.19824.

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Object rearrangement is important for many applications but remains challenging, especially in confined spaces, such as shelves, where objects cannot be accessed from above and they block reachability to each other. Such constraints require many motion planning and collision checking calls, which are computationally expensive. In addition, the arrangement space grows exponentially with the number of objects. To address these issues, this work introduces a lazy evaluation framework with a local monotone solver and a global planner. Monotone instances are those that can be solved by moving each

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Geng, Zihang, Zhiyuan Yang, Wei Xu, Weichao Guo, and Xinjun Sheng. "A Globally Guided Dual-Arm Reactive Motion Controller for Coordinated Self-Handover in a Confined Domestic Environment." Biomimetics 9, no. 10 (2024): 629. http://dx.doi.org/10.3390/biomimetics9100629.

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Future humanoid robots will be widely deployed in our daily lives. Motion planning and control in an unstructured, confined, and human-centered environment utilizing dexterity and a cooperative ability of dual-arm robots is still an open issue. We propose a globally guided dual-arm reactive motion controller (GGDRC) that combines the strengths of global planning and reactive methods. In this framework, a global planner module with a prospective task horizon provides feasible guidance in a Cartesian space, and a local reactive controller module addresses real-time collision avoidance and coordi

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Aghi, Diego, Vittorio Mazzia, and Marcello Chiaberge. "Local Motion Planner for Autonomous Navigation in Vineyards with a RGB-D Camera-Based Algorithm and Deep Learning Synergy." Machines 8, no. 2 (2020): 27. http://dx.doi.org/10.3390/machines8020027.

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With the advent of agriculture 3.0 and 4.0, in view of efficient and sustainable use of resources, researchers are increasingly focusing on the development of innovative smart farming and precision agriculture technologies by introducing automation and robotics into the agricultural processes. Autonomous agricultural field machines have been gaining significant attention from farmers and industries to reduce costs, human workload, and required resources. Nevertheless, achieving sufficient autonomous navigation capabilities requires the simultaneous cooperation of different processes; localizat

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Fu, Yue-wen, Meng Li, Jia-hong Liang, and Xiao-qian Hu. "A Grid-Based Motion Planning Approach for Coherent Groups." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/416913.

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This paper presents a novel motion planning approach for coherent groups with constant area, and it integrates C-L method into the probabilistic roadmap algorithm with sampling on the medial axis (MAPRM). In the preprocessing phase, the group is discretized into a grid-set which represents the configuration of the group. Then, a number of samples are generated on workspace by medial axis technique. These samples are extended into group’s configuration nodes of the roadmap using an extending strategy. Also, the group's deformation degree relative to the desired shape is introduced to improve th

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Sánchez López, Abraham, Alfredo Toriz Palacios, and Rogelio González Velázquez. "20 Years of Integrated Exploration." International Journal of Combinatorial Optimization Problems and Informatics 16, no. 1 (2025): 90–99. https://doi.org/10.61467/2007.1558.2025.v16i1.588.

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The autonomous construction of environment maps with the help of mobile robots is an important problem in modern robotics; because practically all tasks performed by robots require a representation of the working environment. Many solutions have been proposed to solve this problem known as SLAM (Simultaneous Localization and Mapping). The inclusion of a motion planner to the classical SLAM problem gives way to a new approach known as “Integrated Exploration”, in which a robot gradually builds a map while simultaneously localizing itself and making local decisions on where to go to maximize the

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Rohankumar Patel and Ankur Patel. "Assessing ligand Traversability in protein tunnels: A motion planning approach." Global Journal of Engineering and Technology Advances 15, no. 3 (2023): 217–27. https://doi.org/10.30574/gjeta.2023.15.3.0096.

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This paper presents a clever movement arranging framework to evaluate the traversability of ligand molecules within protein tunnels, utilizing the Haloalkane dehalogenase protein (PDB ID 1CQW) as a case study. The approach involves defining key metrics such as accessibility, throughput, and ligand scale to assess local and global traversability of tunnel segments. By implementing a planner that scales ligand radii, we systematically analyze the impact of various scaling factors on the success rates of ligand trajectories. Visualization techniques, including color mapping of tunnel properties a

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Angela, Makolo, and Ojobo Obotu. "Motion Planning In Metabolic Pathways Using Probabilistic Roadmap and A* Algorithms." International Journal of Computer Science Issues 17, no. 6 (2020): 48–57. https://doi.org/10.5281/zenodo.4431061.

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Motion planning and navigation strategies have found useful applications in many areas such as biological networks. This work applies motion planning algorithms to search for biochemically relevant pathways in metabolic pathways. The choice pathways are represented as graphs with its compounds as nodes (vertices), and the possible reactions between the compounds as the edges. The probabilistic roadmap (PRM) algorithm is then used to construct the roadmap (graph) using its local planner function while modelling a group of pool metabolites as obstacles. A* search algorithm queries the roadmap to

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César-Tondreau, Brian, Garrett Warnell, Kevin Kochersberger, and Nicholas R. Waytowich. "Towards Fully Autonomous Negative Obstacle Traversal via Imitation Learning Based Control." Robotics 11, no. 4 (2022): 67. http://dx.doi.org/10.3390/robotics11040067.

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Current research in experimental robotics has had a focus on traditional, cost-based, navigation methods. These methods ascribe a value of utility for occupying certain locations in the environment. A path planning algorithm then uses this cost function to compute an optimal path relative to obstacle positions based on proximity, visibility, and work efficiency. However, tuning this function to induce more complex navigation behaviors in the robot is not straightforward. For example, this cost-based scheme tends to be pessimistic when assigning traversal cost to negative obstacles. Its often s

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Aine, Sandip, Charupriya Sharma, and Maxim Likhachev. "Learning to Search More Efficiently from Experience: A Multi-heuristic Approach." Proceedings of the International Symposium on Combinatorial Search 6, no. 1 (2021): 141–45. http://dx.doi.org/10.1609/socs.v6i1.18376.

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Learning from experience can significantly improve the performance of search based planners, especially for challenging problems like high-dimensional planning. Experience Graph (E-Graph) is a recently developed framework that encodes experiences, obtained from solving instances in the past, into a single bounded-admissible heuristic, and uses it to guide the search. While the E-Graph approach was shown to be very useful for repetitive problems, it suffers from two issues. First, computing the E-Graph heuristic is time consuming as it maintains the bounded admissibility constraints. Second, a

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Wang, Kezhi, Jianyu Li, Meng Xu, Zonghai Chen, and Jikai Wang. "LiDAR-Only Ground Vehicle Navigation System in Park Environment." World Electric Vehicle Journal 13, no. 11 (2022): 201. http://dx.doi.org/10.3390/wevj13110201.

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In this paper, a novel and complete navigation system is proposed for mobile ground vehicles in a park environment. LiDAR map representation and maintenance, dynamic objects detection and removal, hierarchal path planning and model-free local planning are developed in the system. The system is formulated in three layers. In the global layer, given the global point cloud map of the environment, the traverse area is detected and its skeleton graph is extracted to represent the global topology of the environment. Then, in the middle layer, the global map is divided into several submaps and each s

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McMahon, Troy, Shawna Thomas, and Nancy M. Amato. "Sampling-based motion planning with reachable volumes for high-degree-of-freedom manipulators." International Journal of Robotics Research 37, no. 7 (2018): 779–817. http://dx.doi.org/10.1177/0278364918779555.

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Motion planning for constrained systems is a version of the motion planning problem in which the motion of a robot is limited by constraints. For example, one can require that a humanoid robot such as a PR2 remain upright by constraining its torso to be above its base or require that an object such as a bucket of water remain upright by constraining the vertices of the object to be parallel to the robot’s base. Grasping can be modeled by requiring that the end effectors of the robot be located at specified handle positions. Constraints might require that the robot remain in contact with a surf

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Zhang, Qinglei, Siyao Hu, Jianguo Duan, Jiyun Qin, and Ying Zhou. "A SAC-Bi-RRT Two-Layer Real-Time Motion Planning Approach for Robot Assembly Tasks in Unstructured Environments." Actuators 14, no. 2 (2025): 59. https://doi.org/10.3390/act14020059.

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Due to the uncertainty and complexity of the assembly process, the trajectory planning of a robot needs to consider the real-time obstacle avoidance problem when it completes the assembly in the unstructured workspace. To realize the safe assembly of assembly robots in dynamic and complex environments, a dynamic obstacle avoidance trajectory planning method for robots combining traditional planning algorithms and deep reinforcement learning algorithms is proposed to improve the robot’s agent and obstacle avoidance ability in dynamic and complex environments. The Bidirectional Rapidly-exploring

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Arslan, Omur, and Daniel E. Koditschek. "Sensor-based reactive navigation in unknown convex sphere worlds." International Journal of Robotics Research 38, no. 2-3 (2018): 196–223. http://dx.doi.org/10.1177/0278364918796267.

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We construct a sensor-based feedback law that provably solves the real-time collision-free robot navigation problem in a compact convex Euclidean subset cluttered with unknown but sufficiently separated and strongly convex obstacles. Our algorithm introduces a novel use of separating hyperplanes for identifying the robot’s local obstacle-free convex neighborhood, affording a reactive (online-computed) continuous and piecewise smooth closed-loop vector field whose smooth flow brings almost all configurations in the robot’s free space to a designated goal location, with the guarantee of no colli

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