The complexity of robot motion planning
The complexity of robot motion planning
Gross motion planning—a survey
ACM Computing Surveys (CSUR)
Robot motion planning: a distributed representation approach
International Journal of Robotics Research
Planning motions with intentions
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Handbook of discrete and computational geometry
On finding narrow passages with probabilistic roadmap planners
WAFR '98 Proceedings of the third workshop on the algorithmic foundations of robotics on Robotics : the algorithmic perspective: the algorithmic perspective
An algorithm for planning collision-free paths among polyhedral obstacles
Communications of the ACM
Robot Motion Planning
Practical Motion Planning in Robotics: Current Approaches and Future Directions
Practical Motion Planning in Robotics: Current Approaches and Future Directions
Enhancing Randomized Motion Planners: Exploring with Haptic Hints
Autonomous Robots
Complexity of the mover's problem and generalizations
SFCS '79 Proceedings of the 20th Annual Symposium on Foundations of Computer Science
Robust output maneuvering for a class of nonlinear systems
Automatica (Journal of IFAC)
Development of active 80-faced polyhedron for haptic physical human-machine interface
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Design and analysis of an fMRI compatible haptic robot
Robotics and Computer-Integrated Manufacturing
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The motivation of this work arises from the fact that it is very difficult for an automatic path planning method, e.g. probabilistic roadmap (PRM) to generate an optimized path, and sometimes it even fails for an automatic method to find a collision-free path, due to failure of discovering critical robot configurations. However, these critical configurations might be plain to an operator. Therefore, the advantages of human's intuition are exploited to facilitate the robot path planning process in this research. The objective of this paper is to combine the advantages of human's intuition or experiences and the huge computational power of computers to develop a semi-automatic robot path planner that can generate an user-preferred collision-free robot path. In the path planning process, the user interaction is made easy by the development of a haptically controlled virtual robot. By virtual tele-robot manipulation, a user can define or modify critical robot configurations based on which collision-free robot path can be automatically generated.