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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Path planning for non-circular micro aerial vehicles in constrained environments
TL;DR: This work uses an anytime planner based on A* that performs a graph search on a four-dimensional (4-D) (x,y,z, heading) lattice that allows for the generation of close-to-optimal trajectories based on a set of precomputed motion primitives along with the capability to provide trajectories in real-time allowing for on-the-fly re-planning as new sensor data is received.
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Sampling-based planning, control and verification of hybrid systems
TL;DR: A sampling-based approach to planning, control and verification inspired by robotics motion planning algorithms such as rapidly exploring random trees (RRTs) and probabilistic roadmaps (PRMs) is surveyed and how to adapt them to solve standard non-linear control problems is demonstrated.
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TL;DR: The goal of this paper is to permit visually convincing paths to be efficiently computed in a multi-layered environment such as an airport or aMulti-storey building.
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Modeling protein conformational ensembles: from missing loops to equilibrium fluctuations.
TL;DR: Results presented in this work suggest that the proposed methods can provide insight into the interplay between protein flexibility and function.
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Capture of homotopy classes with probabilistic road map
TL;DR: This work focuses here on the open question of building probabilistic roadmaps which can provide an exhaustive list of all the solutions which can not be distorted from one to another while staying collision free and proposes a new algorithm for creating such roadmaps.
References
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Book
Robot Motion Planning
TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
Journal ArticleDOI
An algorithm for planning collision-free paths among polyhedral obstacles
TL;DR: A collision avoidance algorithm for planning a safe path for a polyhedral object moving among known polyhedral objects that transforms the obstacles so that they represent the locus of forbidden positions for an arbitrary reference point on the moving object.
Journal ArticleDOI
Spatial Planning: A Configuration Space Approach
TL;DR: In this article, the authors propose an approach based on characterizing the position and orientation of an object as a single point in a configuration space, in which each coordinate represents a degree of freedom in the position or orientation of the object.
Journal ArticleDOI
Exact robot navigation using artificial potential functions
Elon Rimon,Daniel E. Koditschek +1 more
TL;DR: A methodology for exact robot motion planning and control that unifies the purely kinematic path planning problem with the lower level feedback controller design is presented.
Book
Spatial planning: a configuration space approach
TL;DR: Algorithms for computing constraints on the position of an object due to the presence of ther objects, which arises in applications that require choosing how to arrange or how to move objects without collisions are presented.