Results 21 to 30 of about 846,962 (280)

IMPROVING MOVEMENT OF WHEELED GROUND ROBOTS ON SLOPES USING LIDAR TECHNOLOGY: MAPPING, PLANNING, AND OPTIMIZATION

Iraqi Journal for Computers and Informatics, 2023
The development of wheeled ground robots has enabled them to be used for a variety of tasks. These robots must be able to move with accuracy and precision, especially when faced with obstacles or inclines.
Motion planning Israa M. Abdalameer, Murooj Khalid Ibraheem   +1 more
doaj  

Comprehensive Ocean Information-Enabled AUV Motion Planning Based on Reinforcement Learning

Remote Sensing, 2023
Motion planning based on the reinforcement learning algorithms of the autonomous underwater vehicle (AUV) has shown great potential. Motion planning algorithms are primarily utilized for path planning and trajectory-tracking.
Yun Li, Xinqi He, Zhenkun Lu, Peiguang Jing, Yishan Su   +4 more
doaj   +1 more source

Using Genetic Algorithms with Variable-length Individuals for Planning Two-Manipulators Motion [PDF]

, 1998
International Conference on Artificial Neural Networks and Genetic Algorithms. 01/01/1997. NorwichA method based on genetic algorithms for obtaining coordinated motion plans of manipulator robots is presented. A decoupled planning approach has been used;
Camacho, Eduardo F., Ridao Carlini, Miguel Ángel, Riquelme Santos, José Cristóbal, Toro Bonilla, Miguel   +3 more
core   +1 more source

Sampling-based Algorithms for Optimal Motion Planning [PDF]

, 2011
During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness.
Abramowitz M, Alterovitz R., Arya S., Arya S., Balister P., Berenson D., Berenson D., Branicky MS, Branicky MS, Brooks R., Bruce J., Bry A., Canny J., Choset H., Cortes J., Emilio Frazzoli, Ferguson D., Grimmett G., Henze N., Hsu D., Hsu D., Karaman S., Karaman S., Karaman S., Karaman S., Kavraki L., Koren Y., LaValle SM, Lee DT, Likhachev M., Lin MC, Liu Y., Luders B., Munkres JR, Plaku E., Reif JH, Resnick SI, Sahimi M., Samet H., Samet H., Schrijver A., Sertac Karaman, Shkolnik A., Stentz D., Stilman M., Stoyan D., Tedrake R., Teller S., Urmson C., Wedge NA, Yershova A., Zucker M.   +51 more
core   +3 more sources

Survey of UAV motion planning

IET Cyber-systems and Robotics, 2020
Motion planning is a vital module for unmanned aerial vehicles (UAVs), especially in scenarios of autonomous navigation and operation. This survey delivers some recent state-of-the-art UAV motion planning algorithms and related applications.
Lun Quan, Luxin Han, Boyu Zhou, Shaojie Shen, Fei Gao   +4 more
doaj   +1 more source

Motion planning in tori

, 2007
Let X be a subcomplex of the standard CW-decomposition of the n-dimensional torus. We exhibit an explicit optimal motion planning algorithm for X. This construction is used to calculate the topological complexity of complements of general position ...
Cohen, Daniel C., Pruidze, Goderdzi
core   +4 more sources

Drive the Drive: From Discrete Motion Plans to Smooth Drivable Trajectories

Robotics, 2014
Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy and ...
Henrik Andreasson, Jari Saarinen, Marcello Cirillo, Todor Stoyanov, Achim J. Lilienthal   +4 more
doaj   +1 more source

Motion Planning for an Unmanned Surface Vehicle with Wind and Current Effects

Journal of Marine Science and Engineering, 2022
Aiming at the problem that unmanned surface vehicle (USV) motion planning is disturbed by effects of wind and current, a USV motion planning method based on regularization-trajectory cells is proposed.
Shangding Gu, Chunhui Zhou, Yuanqiao Wen, Changshi Xiao, Alois Knoll   +4 more
doaj   +1 more source

UaMPNet: Uncertainty-Aware Motion Planning Network for Manipulator Motion Planning

IEEE Access
In this study, we propose the Uncertainty-aware Motion Planning Network (UaMPNet) to address the challenges of learning-based motion planning in out-of-distribution scenarios, such as novel environments, with a primary focus on enhancing motion planning ...
Eunhoo Lee, Hyunseok Yang
doaj   +1 more source

Survey of optimal motion planning

IET Cyber-systems and Robotics, 2019
Optimal motion planning becomes more and more important these days and is critical for motion planning algorithms developed in the academia to be applicable to real-world applications.
Yajue Yang, Jia Pan, Weiwei Wan
doaj   +1 more source