Probabilistic roadmaps for path planning in high-dimensional configuration spaces

Kavraki, Lydia E.; Švestka, P.; Latombe, Jean‐Claude; Overmars, Mark H.

doi:10.1109/70.508439

Cited by 5,005 publications

(3,078 citation statements)

References 32 publications

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“…Some approaches make use of randomized planning techniques, e.g. [1,2], other approaches use reactive schemes, for instance [3][4][5], and/or make use of a navigation function to follow a path like [6] or plan directly in the velocity space like [7][8][9][10]. Yet other approaches employ a search, some in physical space, some in configuration space.…”

Section: Related Workmentioning

confidence: 99%

Robust Collision Avoidance in Unknown Domestic Environments

Jacobs

Ferrein

Schiffer

et al. 2010

RoboCup 2009: Robot Soccer World Cup XIII

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Abstract. Service robots operating in domestic indoor environments must be endowed with a safe collision avoidance and navigation method that is reactive enough to avoid contacts with the furniture of the apartment and humans that suddenly appear in front of the robot. Moreover, the method should be local, i.e. should not need a predefined map of the environment. In this paper we describe a navigation and collision avoidance method which is all of that: safe, fast, and local. Based on a geometric grid representation which is derived from the laser range finder of our domestic robot, a path to the next target point is found by employing A * . The obstacles which are used in the local map of the robot are extended depending on the speed the robot travels at. We compute a triangular area in front of the robot which is guaranteed to be free of obstacles. This triangle serves as the space of feasible solutions when searching for the next drive commands. With this triangle, we are able to decouple the path search from the search for drive commands, which tremendously decreases the complexity. We used the proposed method for several years in RoboCup@Home where it was a key factor to our success in the competitions.

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Section: Related Workmentioning

confidence: 99%

Robust Collision Avoidance in Unknown Domestic Environments

Jacobs

Ferrein

Schiffer

et al. 2010

RoboCup 2009: Robot Soccer World Cup XIII

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“…To alleviate this problem, we use feedback-based information roadmaps (FIRMs) [1]. FIRMs generalise probabilistic roadmaps (PRMs) [12] to account for motion and sensing uncertainty. In most of the works considering PRM-based methods and imperfect state information, each edge of the graph depends on the path traveled by the system, i.e., actions and observations taken from the initial belief, and therefore recalculation is necessary when the initial belief changes.…”

Section: Feedback-based Information Roadmapmentioning

confidence: 99%

Sampling-Based Reactive Motion Planning with Temporal Logic Constraints and Imperfect State Information

Montana

Dodd

2017

Lecture Notes in Computer Science

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ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. Abstract. This paper presents a method that allows mobile systems with uncertainty in motion and sensing to react to unknown environments while high-level specifications are satisfied. Although previous works have addressed the problem of synthesising controllers under uncertainty constraints and temporal logic specifications, reaction to dynamic environments has not been considered under this scenario. The method uses feedback-based information roadmaps (FIRMs) to break the curse of history associated with partially observable systems. A transition system is incrementally constructed based on the idea of FIRMs by adding nodes on the belief space. Then, a policy is found in the product Markov decision process created between the transition system and a Rabin automaton representing a linear temporal logic formula. The proposed solution allows the system to react to previously unknown elements in the environment. To achieve fast reaction time, a FIRM considering the probability of violating the specification in each transition is used to drive the system towards local targets or to avoid obstacles. The method is demonstrated with an illustrative example.

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“…where, 1 r is the working radius of the telescopic crane, 2 r is the length of the crane's boomarm, and wgt L is the length of the equipment lifted.…”

Section: Planning Path Using Bihrrtmentioning

confidence: 99%

“…However, these deterministic algorithms can not cope with the "exponential explosion" problem, and they can only find the exact solution in low-dimensional space or under special conditions. To this end, some approaches based-sampling are proposed, such as Probabilistic Road Map (PRM) [1], Rapidly-exploring Random Tree (RRT) [2]. Unlike PRM, RRT does not require the preprocessing of building roadmap, but follows the state equations of control theory and generate new states increasingly under the controlling amount until reaching the target.…”

Section: Introductionmentioning

confidence: 99%

Lift Path Planning for Telescopic Crane Based-on Improved hRRT

Lin¹,

Wang²,

Wu³

et al. 2013

IJCTE

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Abstract-The hRRT algorithms based on heuristics can solve many path planning problems, but its efficiency can still be improved. We deeply analyze the details of hRRT, and enhance it by using bi-directional tree and adopting kd-tree as secondary data structure to select nearest neighbors. At last, the improved hRRT is used for lift path planning for telescopic crane, and the efficiency of the improved hRRT is verified. The result of the experiment shows that the enhanced hRRT can dramatically shorten the plan time without reducing the quality of path.Index Terms-Rapidly-exploring random tree, hRRT, path planning, crane lifting.

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Probabilistic roadmaps for path planning in high-dimensional configuration spaces

Cited by 5,005 publications

References 32 publications

Robust Collision Avoidance in Unknown Domestic Environments

Robust Collision Avoidance in Unknown Domestic Environments

Sampling-Based Reactive Motion Planning with Temporal Logic Constraints and Imperfect State Information

Lift Path Planning for Telescopic Crane Based-on Improved hRRT

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