Probabilistic roadmaps for path planning in high-dimensional configuration spaces
Lydia E. Kavraki,P. Svestka,Jean-Claude Latombe,Mark H. Overmars +3 more
- Vol. 12, Iss: 4, pp 566-580
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TLDR
Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (/spl ap/150 MIPS), after learning for relatively short periods of time (a few dozen seconds).Abstract:
A new motion planning method for robots in static workspaces is presented. This method proceeds in two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collision-free configurations and whose edges correspond to feasible paths between these configurations. These paths are computed using a simple and fast local planner. In the query phase, any given start and goal configurations of the robot are connected to two nodes of the roadmap; the roadmap is then searched for a path joining these two nodes. The method is general and easy to implement. It can be applied to virtually any type of holonomic robot. It requires selecting certain parameters (e.g., the duration of the learning phase) whose values depend on the scene, that is the robot and its workspace. But these values turn out to be relatively easy to choose, Increased efficiency can also be achieved by tailoring some components of the method (e.g., the local planner) to the considered robots. In this paper the method is applied to planar articulated robots with many degrees of freedom. Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (/spl ap/150 MIPS), after learning for relatively short periods of time (a few dozen seconds).read more
Citations
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Constraint-Based Motion Planning Using Voronoi Diagrams
Maxim Garber,Ming C. Lin +1 more
TL;DR: The approach is to reformulate the motion planning problem as a simulation of a constrained dynamical system, and guide this system using generalized Voronoi diagrams (GVDs), which works well in dynamic environments with moving obstacles and is applicable to planning scenarios where multiple robots must move simultaneously to achieve a collision free path.
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Automatic assembly path planning for wiring harness installations
TL;DR: In this article, a low-dimensional path planning algorithm is proposed to find a smooth and collision-free mounting of connectors in a wiring harness installation, which has been implemented and successfully applied to an industrial test case.
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Path Planning for UAVs for Maximum Information Collection
TL;DR: The path planning problem for a single unmanned air vehicle (UAV) is studied with the proposal of novel evolutionary operators: pull-to-desired-region, push-from-forbidden-region (PFFR), and pull- to-final-point (PTFP).
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Path Planning for Autonomous Driving in Unknown Environments
TL;DR: A practical path-planning algorithm that generates smooth paths for an autonomous vehicle operating in an unknown environment, where obstacles are detected online by the robot’s sensors is described.
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From Dynamic Programming to RRTs: Algorithmic Design of Feasible Trajectories
TL;DR: This paper summarizes the recent development of algorithms that construct feasible trajectories for problems that involve both differential constraints and global constraints, and dynamic programming approaches are described that produce approximately-optimal solutions for low-dimensional problems.
References
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Robot Motion Planning
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Journal ArticleDOI
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Elon Rimon,Daniel E. Koditschek +1 more
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