ME‐MADDPG: An efficient learning‐based motion planning method for multiple agents in complex environments

2021 ◽  
Author(s):  
Kaifang Wan ◽  
Dingwei Wu ◽  
Bo Li ◽  
Xiaoguang Gao ◽  
Zijian Hu ◽  
...  
Keyword(s):  
Motion Planning ◽  
Planning Method ◽  
Complex Environments ◽  
Multiple Agents ◽  
Efficient Learning

ADD-RRV for motion planning in complex environments

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Peng Cai ◽  
Xiaokui Yue ◽  
Hongwen Zhang
Keyword(s):  
Principal Component Analysis ◽  
Motion Planning ◽  
Configuration Space ◽  
Principal Component ◽  
Component Analysis ◽  
Planning Method ◽  
Complex Environments ◽  
Local Configuration ◽  
Narrow Passage

Abstract In this paper, we present a novel sampling-based motion planning method in various complex environments, especially with narrow passages. We use online the results of the planner in the ADD-RRT framework to identify the types of the local configuration space based on the principal component analysis (PCA). The identification result is then used to accelerate the expansion similar to RRV around obstacles and through narrow passages. We also propose a modified bridge test to identify the entrance of a narrow passage and boost samples inside it. We have compared our method with known motion planners in several scenarios through simulations. Our method shows the best performance across all the tested planners in the tested scenarios.

A Dataset Generation Tool for Deep learning-based Motion Planning in Complex Environments

2021 ◽  
Author(s):  
Muhammad Usman Sarwar ◽  
Moman Sohail ◽  
Muhayy Ud Din ◽  
Jan Rosell ◽  
Wajahat M Qazi
Keyword(s):  
Deep Learning ◽  
Motion Planning ◽  
Complex Environments

Research on autonomous exploration motion planning method of mobile robots for unstructured scenarios

2021 ◽  
Author(s):  
Xuehao Sun ◽  
Shuchao Deng ◽  
Baohong Tong ◽  
Shuang Wang ◽  
Shuai Ma ◽  
...  
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Planning Method ◽  
Autonomous Exploration

Kinematics Analysis and Motion Control of a Mobile Robot Driven by Three Tracked Vehicles

2018 ◽  
Author(s):  
Xin-Jun Liu ◽  
Zhao Gong ◽  
Fugui Xie ◽  
Shuzhan Shentu
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Degrees Of Freedom ◽  
Inverse Kinematic ◽  
Planning Method ◽  
Tracked Vehicles ◽  
Loop Control ◽  
Point Motion ◽  
Point To Point ◽  
Motion Mode

In this paper, a mobile robot named VicRoB with 6 degrees of freedom (DOFs) driven by three tracked vehicles is designed and analyzed. The robot employs a 3-PPSR parallel configuration. The scheme of the mechanism and the inverse kinematic solution are given. A path planning method of a single tracked vehicle and a coordinated motion planning of three tracked vehicles are proposed. The mechanical structure and the electrical architecture of VicRoB prototype are illustrated. VicRoB can achieve the point-to-point motion mode and the continuous motion mode with employing the motion planning method. The orientation precision of VicRoB is measured in a series of motion experiments, which verifies the feasibility of the motion planning method. This work provides a kinematic basis for the orientation closed loop control of VicRoB whether it works on flat or rough road.

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