Sparse Roadmap Spanners

Dobson, Andrew; Krontiris, Athanasios; Bekris, Kostas E.

doi:10.1007/978-3-642-36279-8_17

Cited by 37 publications

(18 citation statements)

References 12 publications

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“…Each node of the graph is found by using a different state sampler (e.g., uniform, gauss, and obstacle based). We can find the PRM method [11][12][13], SPARS method [14][15][16], RRT method [13,[17][18][19][20], SBL method [21], EST method [22], KPIECE method [23], and SyCLOP method [24].…”

Section: Related Workmentioning

confidence: 99%

The Optimal Collision Avoidance Trajectory Planning of Redundant Manipulators in the Process of Grinding Ceramic Billet Surface

Diao

Chen

et al. 2017

Mathematical Problems in Engineering

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The intelligent manufacturing system (IMS) is widely used in the surface machining of the workpiece. In the process of ceramic surface grinding, the intelligent machine (manipulator) in IMS is required to automatically plan the collision avoidance trajectory in a complex environment. This paper presents an optimal trajectory planning method of the use of redundant manipulators in the surface grinding of ceramic billet, which is based on trajectory evaluation. The collision avoidance trajectory can be optimized, taking into account several parameters in the trajectory, including the length of the collision avoidance path, the weighted sum of the strokes of all joints, and the duration of the collision avoidance trajectory. Firstly, get the planning task. Secondly, set the planning parameters and obtain a number of collision avoidance trajectories. Finally, the evaluation function is used to evaluate the collision avoidance trajectories and get the optimal collision avoidance trajectory. The performance of the proposed optimal collision avoidance trajectory planning method is validated in different evaluation functions.

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Section: Related Workmentioning

confidence: 99%

The Optimal Collision Avoidance Trajectory Planning of Redundant Manipulators in the Process of Grinding Ceramic Billet Surface

Diao

Chen

et al. 2017

Mathematical Problems in Engineering

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“…Existing work has showed that IRS provides orders of magnitude sparser data structures [15], which has a direct relation to online query resolution time, and, in practice, the degradation in path quality is significantly smaller than the theoretical guarantee provided by the stretch factor. Furthermore, a recent variant of the approach can be constructed significantly faster than PRM ) [6], which, in the context of a robot-cloud synergistic computation, would allow a faster refresh rate of the roadmap by providing sensing updates.…”

Section: Effects Of Roadmap Properties On Cloud-based Schemesmentioning

confidence: 99%

Cloud Automation: Precomputing Roadmaps for Flexible Manipulation

Bekris

Shome

Krontiris

et al. 2015

IEEE Robot. Automat. Mag.

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T he goal of this article is to highlight the benefits of cloud automation for industrial adopters and some of the research challenges that must be addressed in this process. The focus is on the use of cloud computing for efficiently planning the motion of new robot manipulators designed for flexible manufacturing floors. In particular, different ways that a robot can interact with a computing cloud are considered, where an architecture that splits computation between the remote cloud and the robot appears advantageous. Given this synergistic robot-cloud architecture, this article describes how solutions from the recent literature can be employed on the cloud during a periodically updated preprocessing phase to efficiently answer manipulation queries on the robot given changes in the workspace. In this setup, interesting tradeoffs arise between path quality and computational efficiency, which are evaluated through simulation. These tradeoffs motivate further research on how motion planning should be executed given access to a computing cloud.

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“…They apply a graph-spanner algorithm to an existing roadmap to reduce its size. Recently, graph-spanner algorithms have also been incorporated in the construction phase of the roadmap itself [21], [22], [23].…”

Section: A Related Workmentioning

confidence: 99%

Sparsification of motion-planning roadmaps by edge contraction

Shaharabani

Salzman

Agarwal

et al. 2013

2013 IEEE International Conference on Robotics and Automation

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We present Roadmap Sparsification by Edge Contraction (RSEC), a simple and effective algorithm for reducing the size of a motion-planning roadmap. The algorithm exhibits minimal effect on the quality of paths that can be extracted from the new roadmap. The primitive operation used by RSEC is edge contraction-the contraction of a roadmap edge to a single vertex and the connection of the new vertex to the neighboring vertices of the contracted edge. For certain scenarios, we compress more than 98% of the edges and vertices at the cost of degradation of average shortest path length by at most 2%.

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Sparse Roadmap Spanners

Cited by 37 publications

References 12 publications

The Optimal Collision Avoidance Trajectory Planning of Redundant Manipulators in the Process of Grinding Ceramic Billet Surface

The Optimal Collision Avoidance Trajectory Planning of Redundant Manipulators in the Process of Grinding Ceramic Billet Surface

Cloud Automation: Precomputing Roadmaps for Flexible Manipulation

Sparsification of motion-planning roadmaps by edge contraction

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