Proceedings Article10.1109/ROBOT.2005.1570414
The Delayed D* Algorithm for Efficient Path Replanning
Dave Ferguson,Anthony Stentz +1 more
- 18 Apr 2005
- pp 2045-2050
TL;DR: A new replanning algorithm is presented that generates equivalent paths to Focussed Dynamic A* while requiring about half its computation time and incrementally repairs previous paths and focusses these repairs towards the current robot position.
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Abstract: Mobile robots are often required to navigate environments for which prior maps are incomplete or inaccurate. In such cases, initial paths generated for the robots may need to be amended as new information is received that is in conflict with the original maps. The most widely used algorithm for performing this path replanning is Focussed Dynamic A* (D*), which is a generalization of A* for dynamic environments. D* has been shown to be up to two orders of magnitude faster than planning from scratch. In this paper, we present a new replanning algorithm that generates equivalent paths to D* while requiring about half its computation time. Like D*, our algorithm incrementally repairs previous paths and focusses these repairs towards the current robot position. However, it performs these repairs in a novel way that leads to improved efficiency.
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Citations
•Proceedings Article
Anytime dynamic A*: an anytime, replanning algorithm
Maxim Likhachev,Dave Ferguson,Geoff Gordon,Anthony Stentz,Sebastian Thrun +4 more
- 05 Jun 2005
TL;DR: A graph-based planning and replanning algorithm able to produce bounded suboptimal solutions in an anytime fashion that combines the benefits of anytime and incremental planners to provide efficient solutions to complex, dynamic search problems.
Batch Informed Trees (BIT*): Sampling-based optimal planning via the heuristically guided search of implicit random geometric graphs
Jonathan D. Gammell,Siddhartha S. Srinivasa,Timothy D. Barfoot +2 more
- 26 May 2015
TL;DR: Batch Informed Trees (BIT*) as discussed by the authors is a planning algorithm based on unifying graph-and sampling-based planning techniques, which combines the efficient ordered nature of graph-based techniques with the anytime scalability of sampling based algorithms, such as Rapidly-exploring Random Trees (RRT).
452
Batch Informed Trees (BIT*): Sampling-based Optimal Planning via the Heuristically Guided Search of Implicit Random Geometric Graphs
TL;DR: Batch Informed Trees (BIT*), a planning algorithm based on unifying graph- and sampling-based planning techniques, is presented, which can be viewed as an extension of incremental graph-search techniques to continuous problem domains as well as a generalization of existing sampling- based optimal planners.
286
A Guide to Heuristic-based Path Planning
Dave Ferguson,Maxim Likhachev,Anthony Stentz +2 more
- 01 Jan 2005
TL;DR: This work describes a family of recently developed heuristicbased algorithms used for path planning in the real world, and introduces the motivation behind each class of algorithms, and discusses their use on real robotic systems.
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System, method and device for predicting navigational decision-making behavior
Anind K. Dey,James Andrew Bagnell,Brian D. Ziebart +2 more
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TL;DR: In this article, a behavior predicting application predicts the route a drive is going to travel based on driver preferences, such as left-hand turns, avoidance of bridges, etc, as well as the preferred destinations and/or routes traveled in the past.
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References
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Principles of Artificial Intelligence
Nils J. Nilsson
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TL;DR: This classic introduction to artificial intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval.
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•Proceedings Article
The focussed D* algorithm for real-time replanning
Anthony Stentz
- 20 Aug 1995
TL;DR: An extension to D* that focusses the repairs to significantly reduce the total time required for the initial path calculation and subsequent replanning operations for dynamic environments where arc costs can change during the traverse of the solution path.
Multi-robot exploration controlled by a market economy
Robert Zlot,Anthony Stentz,M.B. Dias,Scott M. Thayer +3 more
- 07 Aug 2002
TL;DR: This system is reliable and robust in that it can accommodate dynamic introduction and loss of team members in addition to being able to withstand communication interruptions and failures.
Improved fast replanning for robot navigation in unknown terrain
Sven Koenig,Maxim Likhachev +1 more
- 07 Aug 2002
TL;DR: This paper introduces an alternative to Focussed Dynamic A* that implements the same navigation strategy but is algorithmically different, and shows results that will make D*-like replanning algorithms even more popular and enable robotics researchers to adapt them to additional applications.