Interleaving Motion Planning And Execution For Mobile Robots

1998 ◽  
pp. 124-135
Author(s):  
Raja Chatila ◽  
Maher Khatib
Keyword(s):  
Motion Planning ◽  
Mobile Robots

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

Motion Planning for Cooperative Transportation of a Large Object by Multiple Mobile Robots.

2002 ◽  
Vol 68 (665) ◽  
pp. 165-172
Author(s):  
Atsushi YAMASHITA ◽  
Masaki FUKUCHI ◽  
Jun OTA ◽  
Tamio ARAI ◽  
Hajime ASAMA
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Large Object ◽  
Multiple Mobile Robots ◽  
Cooperative Transportation

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

Performance analysis of fast marching-based motion planning for autonomous mobile robots in ITER scenarios

2015 ◽  
Vol 63 ◽  
pp. 36-49 ◽  
Author(s):  
Javier V. Gómez ◽  
Alberto Vale ◽  
Santiago Garrido ◽  
Luis Moreno
Keyword(s):  
Performance Analysis ◽  
Motion Planning ◽  
Mobile Robots ◽  
Autonomous Mobile Robots ◽  
Fast Marching

Motion Planning for Mobile Robots: A Method for the Selection of a Combination of Motion-Planning Algorithms

2016 ◽  
Vol 23 (4) ◽  
pp. 107-117 ◽  
Author(s):  
J.J.M. Lunenburg ◽  
S.A.M. Coenen ◽  
G.J.L. Naus ◽  
M.J.G. van de Molengraft ◽  
M. Steinbuch
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Planning Algorithms ◽  
Selection Of

scholarly journals The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation

2020 ◽  
Vol 69 ◽  
pp. 471-500
Author(s):  
Shih-Yun Lo ◽  
Shiqi Zhang ◽  
Peter Stone
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Mobile Robots ◽  
Large Scale ◽  
Accurate Estimate ◽  
Indoor Environments ◽  
Task Planning ◽  
Trade Offs ◽  
High Level ◽  
Task Level

Intelligent mobile robots have recently become able to operate autonomously in large-scale indoor environments for extended periods of time. In this process, mobile robots need the capabilities of both task and motion planning. Task planning in such environments involves sequencing the robot’s high-level goals and subgoals, and typically requires reasoning about the locations of people, rooms, and objects in the environment, and their interactions to achieve a goal. One of the prerequisites for optimal task planning that is often overlooked is having an accurate estimate of the actual distance (or time) a robot needs to navigate from one location to another. State-of-the-art motion planning algorithms, though often computationally complex, are designed exactly for this purpose of finding routes through constrained spaces. In this article, we focus on integrating task and motion planning (TMP) to achieve task-level-optimal planning for robot navigation while maintaining manageable computational efficiency. To this end, we introduce TMP algorithm PETLON (Planning Efficiently for Task-Level-Optimal Navigation), including two configurations with different trade-offs over computational expenses between task and motion planning, for everyday service tasks using a mobile robot. Experiments have been conducted both in simulation and on a mobile robot using object delivery tasks in an indoor office environment. The key observation from the results is that PETLON is more efficient than a baseline approach that pre-computes motion costs of all possible navigation actions, while still producing plans that are optimal at the task level. We provide results with two different task planning paradigms in the implementation of PETLON, and offer TMP practitioners guidelines for the selection of task planners from an engineering perspective.

Sign in / Sign up

Export Citation Format

Share Document