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

scholarly journals A new optimization-driven path planning method with probabilistic completeness for wheeled mobile robots

2019 ◽  
Vol 52 (5-6) ◽  
pp. 317-325 ◽  
Author(s):  
Bo You ◽  
Zhi Li ◽  
Liang Ding ◽  
Haibo Gao ◽  
Jiazhong Xu
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Mobile Robots ◽  
Energy Efficient ◽  
Planning Process ◽  
Planning Method ◽  
Projection Algorithm ◽  
Wheeled Mobile Robots ◽  
Active Set ◽  
Weak Minima

Wheeled mobile robots are widely utilized for environment-exploring tasks both on earth and in space. As a basis for global path planning tasks for wheeled mobile robots, in this study we propose a method for establishing an energy-based cost map. Then, we utilize an improved dual covariant Hamiltonian optimization for motion planning method, to perform point-to-region path planning in energy-based maps. The method is capable of efficiently handling high-dimensional path planning tasks with non-convex cost functions through applying a robust active set algorithm, that is, non-monotone gradient projection algorithm. To solve the problem that the path planning process is locked in weak minima or non-convergence, we propose a randomized variant of the improved dual covariant Hamiltonian optimization for motion planning based on simulated annealing and Hamiltonian Monte Carlo methods. The results of simulations demonstrate that the final paths generated can be time efficient, energy efficient and smooth. And the probabilistic completeness of the method is guaranteed.

Iterative Transportation by Multiple Mobile Robots Considering Unknown Obstacles

2009 ◽  
Vol 21 (1) ◽  
pp. 44-56
Author(s):  
Kousuke Inoue ◽  
◽  
Jun Ota ◽  
Tamio Arai ◽  
Keyword(s):  
Reinforcement Learning ◽  
Motion Planning ◽  
Mobile Robots ◽  
Efficient Method ◽  
Planning Method ◽  
Configuration Spaces ◽  
Path Generation ◽  
Final Phase ◽  
Simulation Results ◽  
Environmental Exploration

The focus in this paper is on a planning method for an iterative transportation task performed by mobile robots in environments including unknown obstacles. This task requires the acquisition of environmental information, the generation of the appropriate path network based on the acquired information, and the formation of a group of robots on the planned path network. To achieve an efficient method of transportation, a motion planning architecture is proposed that includes three phases, i.e., environmental exploration, path generation, and learning of formation. In the first phase, robots cooperatively explore the environment using a learned visibility graph while transporting. Next, a network of transportation paths consisting of 1- and 2-lane paths is generated using two kinds of configuration spaces. In the final phase, every robot learns a behavior strategy by reinforcement learning to acquire an efficient formation of transportation. The simulation results indicate the effectiveness of the proposed architecture.

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.

scholarly journals The WL_PCR: A Planning for Ground-to-Pole Transition of Wheeled-Legged Pole-Climbing Robots

Robotics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 96
Author(s):  
Yankai Wang ◽  
Qiaoling Du ◽  
Tianhe Zhang ◽  
Chengze Xue
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Dynamic Process ◽  
Mathematical Expression ◽  
Truss Structure ◽  
Centre Of Mass ◽  
Climbing Robots ◽  
Wheeled Vehicle ◽  
Motion Modes

Hybrid mobile robots with two motion modes of a wheeled vehicle and truss structure with the ability to climb poles have significant flexibility. The motion planning of this kind of robot on a pole has been widely studied, but few studies have focused on the transition of the robot from the ground to the pole. In this study, a locomotion strategy of wheeled-legged pole-climbing robots (the WL_PCR) is proposed to solve the problem of ground-to-pole transition. By analyzing the force of static and dynamic process in the ground-to-pole transition, the condition of torque provided by the gripper and moving joint is proposed. The mathematical expression of Centre of Mass (CoM) of the wheeled-legged pole-climbing robots is utilized, and the conditions for the robot to smoothly transition from the ground to the vertical pole are proposed. Finally, the feasibility of this method is proved by the simulation and experimentation of a locomotion strategy on wheeled-legged pole-climbing robots.

scholarly journals Motion Planning for a Chain of Mobile Robots Using A* and Potential Field

Robotics ◽  
2018 ◽  
Vol 7 (2) ◽  
pp. 20 ◽  
Author(s):  
A poorva ◽  
Rahul Gautam ◽  
Rahul Kala
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Potential Field ◽  
A Chain
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