The Development of an Autonomous Mobile Crane System Considering On-Line Obstacle Recognition and Path Planning

2008 ◽  
Vol 2 (2) ◽  
pp. 131-140 ◽  
Author(s):  
Akihiro Kaneshige ◽  
◽  
Shigeo Hasegawa ◽  
Kazuhiko Terashima ◽  
Keyword(s):  
Control System ◽  
Path Planning ◽  
Visual System ◽  
Potential Field ◽  
Notch Filter ◽  
Planning Method ◽  
Planning System ◽  
On Line ◽  
Mobile Crane ◽  
Line Path

The purpose of this paper is to present a method to establish an autonomous mobile crane system which includes on-line obstacle recognition, path planning by on-line and suppression of sway of the transferred object. The system consists of three different parts: a visual system, a planning system and a control system. In the visual system, ultra sonic sensor is used to renew small part of environmental map during the transferring taking advantage of quick scanning time. In the planning system, proposed on-line path planning method is used in an artificial potential field based on the solution of the Laplacian differential equation. This path planning method can correspond to minor changes in the transportation environment during transportation. The on-line path planning has been accomplished by regenerating the updated potential field. In the control system, feed-forward controller by means of notch filter is used to achieve the suppression of sway of the transferred object. Finally, the usefulness of the proposed method is confirmed by simulations and experiments.

Comparative analysis of collision-free path-planning methods for multi-manipulator systems

Robotica ◽  
2006 ◽  
Vol 24 (6) ◽  
pp. 711-726 ◽  
Author(s):  
J. C. Fraile ◽  
J. Perez-Turiel ◽  
J. L. Gonzalez-Sanchez ◽  
E. Baeyens ◽  
R. Perez
Keyword(s):  
Comparative Analysis ◽  
Path Planning ◽  
Potential Field ◽  
Degrees Of Freedom ◽  
Dynamic Environments ◽  
Elastic Strip ◽  
Field Methods ◽  
Planning Methods ◽  
On Line ◽  
Line Path

Motion planning for manipulators with many degrees of freedom is a complex task. The research in this area has been mostly restricted to static environments. This paper presents a comparative analysis of three reactive on-line path-planning methods for manipulators: the elastic-strip, strategy-based and potential field methods. Both the elastic-strip method [O. Brock and O. Khatib, “Elastic strips: A framework for integrated planning and execution,” Int. Symp. Exp. Robot. 245–254 (1999)] and the potential field method [O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” Int. J. Robot. Res.5(1), 90–98 (1986)] have been adapted by the authors to the problem at hand related to our multi-manipulator system (MMS) (three manipulators with five degrees of freedom each). Strategy-based method is an original contribution by the authors [M. Mediavilla, J. L. González, J. C. Fraile and J. R. Perán, “Reactive approach to on-line path planning for robot manipulators in dynamic environments,” Robotica20, 375–384 (2002); M. Mediavilla, J. C. Fraile, T. González and I. J. Galindo, “Selection of strategies for collision-free motion in multi-manipulator systems,” J. Intell. Robot Syst38, 85–104 (2003)].The three methods facilitate on-line path planning for our MMS in dynamic environments with collision avoidance, where the three manipulators may move at the same time in their common workspace. We have defined some ‘basic motion problems’ for the MMS, and a series of simulations has been running that will tell us how effective each path-planning method is. The simulations have been performed and the obtained results have been analysed by using a software program developed by the authors.The paper also presents experimental results obtained applying the path-planning methods to our MMS, that perform pick-and-place tasks sharing common working areas.

scholarly journals Path Planning Method With Improved Artificial Potential Field—A Reinforcement Learning Perspective

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 135513-135523
Author(s):  
Qingfeng Yao ◽  
Zeyu Zheng ◽  
Liang Qi ◽  
Haitao Yuan ◽  
Xiwang Guo ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Potential Field ◽  
Planning Method ◽  
Artificial Potential Field

scholarly journals Collision-Free Path-Planning for Six-DOF Serial Harvesting Robot Based on Energy Optimal and Artificial Potential Field

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Lufeng Luo ◽  
Hanjin Wen ◽  
Qinghua Lu ◽  
Haojie Huang ◽  
Weilin Chen ◽  
...  
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Test System ◽  
Planning Method ◽  
Artificial Potential Field ◽  
Optimal Method ◽  
Planning Algorithm ◽  
Six Dof ◽  
Searching Method ◽  
Harvesting Robot

Collision-free autonomous path planning under a dynamic and uncertainty vineyard environment is the most important issue which needs to be resolved firstly in the process of improving robotic harvesting manipulator intelligence. We present and apply energy optimal and artificial potential field to develop a path planning method for six degree of freedom (DOF) serial harvesting robot under dynamic uncertain environment. Firstly, the kinematical model of Six-DOF serial manipulator was constructed by using the Denavit-Hartenberg (D-H) method. The model of obstacles was defined by axis-aligned bounding box, and then the configuration space of harvesting robot was described by combining the obstacles and arm space of robot. Secondly, the harvesting sequence in path planning was computed by energy optimal method, and the anticollision path points were automatically generated based on the artificial potential field and sampling searching method. Finally, to verify and test the proposed path planning algorithm, a virtual test system based on virtual reality was developed. After obtaining the space coordinates of grape picking point and anticollision bounding volume, the path points were drew out by the proposed method. 10 times picking tests for grape anticollision path planning were implemented on the developed simulation system, and the success rate was up to 90%. The results showed that the proposed path planning method can be used to the harvesting robot.

Sign in / Sign up

Export Citation Format

Share Document