Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Formation Obstacle Avoidance Algorithm Based On Joint Virtual Sub-Target And Boundary Force, Man Wang, Dapeng Li, Lianghui Ding, Tianlin Zhu
Formation Obstacle Avoidance Algorithm Based On Joint Virtual Sub-Target And Boundary Force, Man Wang, Dapeng Li, Lianghui Ding, Tianlin Zhu
Journal of System Simulation
Abstract: In view of the formation control of leader-follower swarm and obstacle avoidance in artificial potential field method in unmanned aerial vehicle (UAV) swarm formation system under complex environmental conditions, an obstacle avoidance algorithm for UAV swarm formation based on joint virtual sub-target and boundary force (JVBF) is proposed. The leader-follower method based on a virtual sub-target is used, and the modified force function is optimized to realize the formation control of the UAV swarm, so as to help the follower UAV to recover the formation quickly; the artificial potential field method based on boundary force is used for local …
Virtual Navigation Path Planning Based On Octree Potential Field For Endonasal Endoscope, Wenjing Li, Yanlin Luo, Yuhui Wang, Li Zhu
Virtual Navigation Path Planning Based On Octree Potential Field For Endonasal Endoscope, Wenjing Li, Yanlin Luo, Yuhui Wang, Li Zhu
Journal of System Simulation
Abstract: Virtual navigation can intuitively display the internal structure of human tissue from multiple viewpoints. The navigation path planning algorithm is the key to achieving excellent navigation effects. The traditional centerline extraction algorithm can ensure a wide field of view during navigation, but the time efficiency is not high enough on the complex nasal-skull base volume model. To solve the problem, a rapid navigation path planning algorithm based on the octree potential field is proposed. The space outside the obstacles is modeled by an octree, and the octree potential field is constructed by calculating the potential of all the octree …
Obstacle Avoidance Path Planning And Simulation Of Mobile Picking Robot Based On Dppo, Junqiang Lin, Hongjun Wang, Xiangjun Zou, Po Zhang, Chengen Li, Yipeng Zhou, Shujie Yao
Obstacle Avoidance Path Planning And Simulation Of Mobile Picking Robot Based On Dppo, Junqiang Lin, Hongjun Wang, Xiangjun Zou, Po Zhang, Chengen Li, Yipeng Zhou, Shujie Yao
Journal of System Simulation
Abstract: Aiming at the autonomous decision-making difficulty of mobile picking robots in random and changeable complicated path environment during field operations, an autonomous obstacle avoidance path planning method based on deep reinforcement learning is propose. By setting the state space and action space and using the artificial potential field method to design the reward function, an obstacle penalty coefficient setting method based on collision cone collision avoidance detection is proposed to improve the autonomous collision avoidance ability. A virtual simulation system is constructed, in which the learning and training of the mobile picking robot is carried out and verified by …
Obstacle Avoidance And Simulation Of Carrier-Based Aircraft On The Deck Of Aircraft Carrier, Junxiao Xue, Xiangyan Kong, Bowei Dong, Hao Tao, Haiyang Guan, Lei Shi, Mingliang Xu
Obstacle Avoidance And Simulation Of Carrier-Based Aircraft On The Deck Of Aircraft Carrier, Junxiao Xue, Xiangyan Kong, Bowei Dong, Hao Tao, Haiyang Guan, Lei Shi, Mingliang Xu
Journal of System Simulation
Abstract: A predictive depth deterministic policy gradient (PDDPG) algorithm is proposed by combining the least squares method with deep deterministic policy gradient(DDPG) for the problems of strong randomness, poor real-time performance, and slow planning speed by obstacle avoidance on aircraft carrier deck. The short-term trajectory of dynamic obstacles on the deck is predicted by the least square method. DDPG is used to provide agents with the ability to learn and make decisions in continuous space by the short-term trajectory of dynamic obstacles. The reward function is set based on the artificial potential field to improve the convergence speed and accuracy …