Beamlet-like data processing for accelerated path-planning using multiscale information of the environment

Lu, Yibiao; Huo, Xiaoming; Tsiotras, Panagiotis

doi:10.1109/cdc.2010.5717586

Cited by 11 publications

(11 citation statements)

References 14 publications

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“…Third, multiresolution processing opens the avenue for more general connectivity relationships between the cells, beyond the standard 4-neighborhood of 8-neighborhood connectivity. See [26] for an implementation on pathplanning problems using beamlet-like connectivity between the nodes in the underlying search graph. Finally, the extension to three-dimensional navigation problems is also possible, albeit somewhat cumbersome.…”

Section: Discussionmentioning

confidence: 99%

Multiresolution Hierarchical Path-Planning for Small UAVs Using Wavelet Decompositions

Tsiotras

Jung

Bakolas

2011

J Intell Robot Syst

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We present an algorithm for solving the shortest (collision-free) path planning problem for an agent (e.g., a small UAV) with limited onboard computational resources. The agent has detailed knowledge of the environment and the obstacles only in the vicinity of its current position. Far away obstacles are only partially known and may even change dynamically. The algorithm makes use of the wavelet transform to construct an approximation of the environment at different levels of resolution. We associate with this multiresolution representation of the environment a graph, whose dimension can be made commensurate to the on-board computational resources of the agent. The adjacency list of the graph can be efficiently constructed directly from the approximation and detail wavelet coefficients, thus further speeding up the whole process. Simulations are presented to test the efficiency of the algorithm using non-trivial scenarios.

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Section: Discussionmentioning

confidence: 99%

Multiresolution Hierarchical Path-Planning for Small UAVs Using Wavelet Decompositions

Tsiotras

Jung

Bakolas

2011

J Intell Robot Syst

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“…TWD * algorithm [19] by using the bidirectional D * search algorithm, simultaneously, can be achieved shorter and more reasonable path in an unknown environment in less time. MA * [28] and m-LPA * algorithms [27] will be simplify graph and improve computational complexity by using the information obtained from analysis of hierarchical multi-scale dyadic squares on the graph, respectively in A * and LPA * algorithm. Finding accurate and efficient algorithm for path planning problem is always a challengeable issue.…”

Section: Related Workmentioning

confidence: 99%

Optimal path planning for mobile robot using Intelligent Water Drops algorithm

Salmanpour¹,

Motameni

2014

Journal of Intelligent &Amp; Fuzzy Systems

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In this paper, the generalized intelligent water drops (IWD) algorithm is proposed to solve robot path planning problem. Path planning is modeled by IWD algorithm, because there is inherent similarity between this and finding most appropriate route in natural rivers, that occurs by interaction between water drops and the river bed. The proposed algorithm has two levels; first level, finds the best global feasible path. Second level, performs local search at relatively near distances of global path and reduces its length and time to reach optimal solution. The IWD algorithm, like other inspired nature algorithms, has not a mechanism to deal with constrained optimization problem in its original version. So, a mechanism has been proposed based on repair of infeasible solutions. In this mechanism, a fuzzy inference system is proposed for selecting the best possible infeasible solution and then the local search operator repairs any of them in violation locations. Another innovation of this paper provides a mechanism to local soil update, which is based on fuzzy systems and is independent of size and complexity of environment and its soil altering will be defined in fixed range. Simulation result shows ability of IWD algorithm in finding of the optimal path.

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“…To solve this problem, Scherer et al propagate actual Euclidean distance from the exact source cell so that relative error can be significantly reduced [22]. Following this improvement, Lau et al in their work proposed novel methods to rebuild GVDs with less computation time and fewer cell visits [6]; different from Kalra's work, their approach does not rely on site identifiers Vertex +ID:int +pos:int [2] +eIDs:list"int" +sIDs:list"int" EdgeMap:map"int,Edge" to detect GVD edges, so edges in the interior of a concave site can be also detected. Furthermore, Boris Lau et al provided additional thinning steps using "thinning patterns" proposed by Zhang and Suen [23] to get one-cell wide edges.…”

Section: Related Workmentioning

confidence: 99%

“…Common representations for describing the environment include (but are not limited to) uniform [1] and nonuniform grid maps [2], probabilistic roadmaps [3], waypoint graph [4], and Generalized Voronoi Diagrams (GVDs). We first give a definition of the GVDs.…”

Section: Introductionmentioning

confidence: 99%

“…The boundary that divides two regions is named as a GVD edge which can be denoted as edge ( , ) = { | ∈ reg ( ) and ∈ reg ( )} . (2) Due to the prevalence of grid-based environment representations in robotics, GVDs built on grids are widely used and outperform the other representations in extracting sparse but adequate environment skeletons [6,7]. The advantages of employing such a skeleton are twofold.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams

Qin

Yin

Zha

et al. 2013

Mathematical Problems in Engineering

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In the context of robotics, the grid-based Generalized Voronoi Diagrams (GVDs) are widely used by mobile robots to represent their surrounding area. Current approaches for incrementally constructing GVDs mainly focus on providing metric skeletons of underlying grids, while the connectivity among GVD vertices and edges remains implicit, which makes high-level spatial reasoning tasks impractical. In this paper, we present an algorithm named Dynamic Topology Detector (DTD) for extracting a GVD with topological information from a grid map. Beyond the construction and reconstruction of a GVD on grids, DTD further extracts connectivity among the GVD edges and vertices. DTD also provides efficient repair mechanism to treat with local changes, making it work well in dynamic environments. Simulation tests in representative scenarios demonstrate that (1) compared with the static algorithms, DTD generally makes an order of magnitude improvement regarding computation times when working in dynamic environments; (2) with negligible extra computation, DTD detects topologies not computed by existing incremental algorithms. We also demonstrate the usefulness of the resulting topological information for high-level path planning tasks.

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Beamlet-like data processing for accelerated path-planning using multiscale information of the environment

Cited by 11 publications

References 14 publications

Multiresolution Hierarchical Path-Planning for Small UAVs Using Wavelet Decompositions

Multiresolution Hierarchical Path-Planning for Small UAVs Using Wavelet Decompositions

Optimal path planning for mobile robot using Intelligent Water Drops algorithm

Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams

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