Robotic exploration as graph construction

Dudek, Gregory; Jenkin, Michael; Milios, Evangelos; Wilkes, D.

doi:10.1109/70.105395

Cited by 233 publications

(173 citation statements)

References 9 publications

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“…We mention only in passing the extensive investigations on exploration and navigation in terrains other than graphs (e.g., [11,14,22,44]), where orientation and sense of direction play an important role.…”

Section: Related Workmentioning

confidence: 99%

Searching for a black hole in arbitrary networks: optimal mobile agents protocols

et al. 2006

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Consider a networked environment, supporting mobile agents, where there is a black hole: a harmful host that disposes of visiting agents upon their arrival, leaving no observable trace of such a destruction. The black hole search problem is the one of assembling a team of asynchronous mobile agents, executing the same protocol and communicating by means of whiteboards, to successfully identify the location of the black hole; we are concerned with solutions that are generic (i.e., topology-independent). We establish tight bounds on the size of the team (i.e., the number of agents), and the cost (i.e., the number of moves) of a size-optimal solution protocol. These bounds depend on the a priori knowledge the agents have about the network, and on the consistency of the local labellings. In particular, we prove that: with topological ignorance ∆ + 1 agents are needed and suffice, and the cost is Θ(n 2 ), where ∆ is the maximal degree of a node and n is the number of nodes in the network; with topological ignorance but in presence of sense of direction only two agents suffice and the cost is Θ(n 2 ); and with complete topological knowledge only two agents suffice and the cost is Θ(n log n). All the upper-bound proofs are constructive.

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Section: Related Workmentioning

confidence: 99%

Searching for a black hole in arbitrary networks: optimal mobile agents protocols

et al. 2006

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“…Instead of focusing on the on-board resources, some part of robotics literature use a single ant or a group of robots to cover an area robustly, even if they do not have any memory, do not know the terrain, cannot maintain maps of the terrain, nor plan complete paths. They use environmental markers such as pebbles [24], [25], [26] or pheromone like traces [27] or greedy navigation strategies [28].…”

Section: Related Workmentioning

confidence: 99%

Stigmergic MASA: A Stigmergy Based Algorithm for Multi-Target Search

Zedadra¹,

Séridi²,

Jouandeau³

et al. 2014

Annals of Computer Science and Information Systems

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Abstract-We explore the on-line problem of coverage where multiple agents have to find a target whose position is unknown, and without a prior global information about the environment. In this paper a novel algorithm for multi-target search is described, it is inspired from water vortex dynamics and based on the principle of pheromone-based communication. According to this algorithm, called S-MASA (Stigmergic Multi Ant Search Area), the agents search nearby their base incrementally using turns around their center and around each other, until the target is found, with only a group of simple distributed cooperative Ant like agents, which communicate indirectly via depositing/detecting markers. This work improves the search performance in comparison with random walk and S-random walk (stigmergic random walk) strategies, we show the obtained results using computer simulations.

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“…In [7], [8] the problem of graph coverage using a few markers is considered. In both cases the authors study the problem of dynamic single robot coverage of an environment consisting of nodes and edges (a graph).…”

Section: Related Workmentioning

confidence: 99%

“…This idea has received attention in coverage and exploration [3], [4], [7], [8], [9], and navigation [3], [10], [11]. Ant-like trail laying algorithms [10], [9] consider a special case of the marker deployment approaches -when the distance between the two consecutive markers is small.…”

Section: Related Workmentioning

confidence: 99%

Using a sensor network for distributed multi-robot task allocation

Batalin

Sukhatme

2004

IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004

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Abstract-We present a Multi Field Distributed In-network Task Allocation (DINTA-MF) algorithm for online multi-robot task allocation (OMRTA) where tasks are allocated explicitly to robots by a pre-deployed, static sensor network. The idea of DINTA-MF is to compute several assignment fields in the sensor network and then distributively assign fields to different robots. Experimental results with a simulated alarm scenario show that our approach is able to compute solutions to the OMRTA problem in a distributed fashion and arguably in an optimal way. We compared DINTA-MF with a simpler implementation (DINTA) which uses one assignment field. The data show that DINTA-MF outperforms DINTA as the number of robots increases.

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Robotic exploration as graph construction

Cited by 233 publications

References 9 publications

Searching for a black hole in arbitrary networks: optimal mobile agents protocols

Searching for a black hole in arbitrary networks: optimal mobile agents protocols

Stigmergic MASA: A Stigmergy Based Algorithm for Multi-Target Search

Using a sensor network for distributed multi-robot task allocation

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