The complexity of robot motion planning
The complexity of robot motion planning
A survey of motion planning and related geometric algorithms
Artificial Intelligence - Special issue on geometric reasoning
Two manipulation planning algorithms
WAFR Proceedings of the workshop on Algorithmic foundations of robotics
Dynamic motion planning in low obstacle density environments
WADS '97 Selected papers presented at the international workshop on Algorithms and data structure
International Journal of Robotics Research
Planning Algorithms
Discrete & Computational Geometry
Computational Geometry: Algorithms and Applications
Computational Geometry: Algorithms and Applications
Complexity of the mover's problem and generalizations
SFCS '79 Proceedings of the 20th Annual Symposium on Foundations of Computer Science
Hybrid systems: from verification to falsification by combining motion planning and discrete search
Formal Methods in System Design
Manipulation planning with workspace goal regions
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Path planning in 1000+ dimensions using a task-space Voronoi bias
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Survivability: measuring and ensuring path diversity
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Reachability-guided sampling for planning under differential constraints
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
On the performance of random linear projections for sampling-based motion planning
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Complementarity-based dynamic simulation for kinodynamic motion planning
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Sampling-Based Roadmap of Trees for Parallel Motion Planning
IEEE Transactions on Robotics
Maneuver-based motion planning for nonlinear systems with symmetries
IEEE Transactions on Robotics
Improving Motion-Planning Algorithms by Efficient Nearest-Neighbor Searching
IEEE Transactions on Robotics
Improving the Performance of Sampling-Based Motion Planning With Symmetry-Based Gap Reduction
IEEE Transactions on Robotics
Delaunay refinement algorithms for triangular mesh generation
Computational Geometry: Theory and Applications
Research paper: Sampling-based robot motion planning: Towards realistic applications
Computer Science Review
Guiding sampling-based motion planning by forward and backward discrete search
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part III
Iterative temporal motion planning for hybrid systems in partially unknown environments
Proceedings of the 16th international conference on Hybrid systems: computation and control
A kind of two-stage RRT algorithm for robotic path planning
International Journal of Wireless and Mobile Computing
Integrated motion planning and control for graceful balancing mobile robots
International Journal of Robotics Research
Exponential fields formulation for WMR navigation
Applied Bionics and Biomechanics - Personal Care Robotics
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To efficiently solve challenges related to motionplanning problems with dynamics, this paper proposes treating motion planning not just as a search problem in a continuous space but as a search problem in a hybrid space consisting of discrete and continuous components. A multilayered framework is presented which combines discrete search and sampling-based motion planning. This framework is called synergistic combination of layers of planning (SyCLoP) hereafter. Discrete search uses a workspace decomposition to compute leads, i.e., sequences of regions in the neighborhood that guide sampling-based motion planning during the state-space exploration. In return, information gathered bymotion planning, such as progress made, is fed back to the discrete search. This combination allows SyCLoP to identify new directions to lead the exploration toward the goal, making it possible to efficiently find solutions, even when other planners get stuck. Simulation experiments with dynamical models of ground and flying vehicles demonstrate that the combination of discrete search and motion planning in SyCLoP offers significant advantages. In fact, speedups of up to two orders of magnitude were obtained for all the sampling-based motion planners used as the continuous layer of SyCLoP.