Elastic roadmaps--motion generation for autonomous mobile manipulation
Autonomous Robots
A path planning approach to (dis) assembly sequencing
CASE'09 Proceedings of the fifth annual IEEE international conference on Automation science and engineering
Encoding molecular motions in voxel maps
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Efficient planning of disassembly sequences in physics-based animation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning
Artificial Intelligence Review
Sampling-based path planning on configuration-space costmaps
IEEE Transactions on Robotics
Evolving robotic path with genetically optimised fuzzy planner
International Journal of Computational Vision and Robotics
Encoding Molecular Motions in Voxel Maps
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Robotic path planning using hybrid genetic algorithm particle swarm optimisation
International Journal of Information and Communication Technology
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Sampling-based path planning algorithms are powerful tools for computing constrained disassembly motions. This paper presents a variant of the rapidly-exploring random tree (RRT) algorithm particularly devised for the disassembly of objects with articulated parts. Configuration parameters generally play two different roles in this type of problems: some of them are essential for the disassembly task, while others only need to move if they hinder the progress of the disassembly process. The proposed method is based on such a partition of the configuration parameters. Results show a remarkable performance improvement as compared to standard path planning techniques. The paper also shows practical applications of the presented algorithm in robotics and structural bioinformatics.