The “Ariadne's clew” algorithm: global planning with local methods
WAFR Proceedings of the workshop on Algorithmic foundations of robotics
Random networks in configuration space for fast path planning
Random networks in configuration space for fast path planning
Motion planning for carlike robots using a probabilistic learning approach
International Journal of Robotics Research
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
OBPRM: an obstacle-based PRM for 3D workspaces
WAFR '98 Proceedings of the third workshop on the algorithmic foundations of robotics on Robotics : the algorithmic perspective: the algorithmic perspective
Robot Motion Planning
The crowd simulation for interactive virtual environments
VRCAI '04 Proceedings of the 2004 ACM SIGGRAPH international conference on Virtual Reality continuum and its applications in industry
Development of a configuration space motion planner for robot in dynamic environment
Robotics and Computer-Integrated Manufacturing
Generating tutoring feedback in an intelligent training system on a robotic simulator
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
An approach to intelligent training on a robotic simulator using an innovative path-planner
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Mobile robot path planning algorithm by equivalent conduction heat flow topology optimization
Structural and Multidisciplinary Optimization
| Hi-index | 0.00 |
Motion planning is becoming an important topic in many application areas, ranging from robotics to virtual environments and games. In this paper I review some recent results in motion planning, concentrating on the probabilistic roadmap approach that has proven to be very successful for many motion planning problems. After a brief description of the approach I indicate how the technique can be applied to various motion planning problems. Next I give a number of global techniques for improving the approach, and finally I describe some recent results on improving the quality of the resulting motions.