In this paper we present a brief survey of the ant based multi-agent exploration algorithms and a performance comparison of these algorithms obtained by analyzing them in a variety of scenarios.
ISBN:
(纸本)9781479975143
In this paper we present a brief survey of the ant based multi-agent exploration algorithms and a performance comparison of these algorithms obtained by analyzing them in a variety of scenarios.
In this paper, we provide an overview of exploration algorithms, a novel class of evolutionary computation approaches encompassing novelty search and quality-diversity, as they may be applied to portfolio optimization...
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Many people are fascinated by biological swarms, but understanding the behavior and inherent task objectives of a bird flock or ant colony requires training. Whereas several swarm intelligence works focus on mimicking...
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Many people are fascinated by biological swarms, but understanding the behavior and inherent task objectives of a bird flock or ant colony requires training. Whereas several swarm intelligence works focus on mimicking natural swarm behaviors, we argue that this may not be the most intuitive approach to facilitate communication with the operators. Instead, we focus on the legibility of swarm expressive motions to communicate mission-specific messages to the operator. To do so, we leverage swarm intelligence algorithms on chain formation for resilient exploration and mapping combined with acyclic graph formation (AGF) into a novel swarm-oriented programming strategy. We then explore how expressive motions of robot swarms could be designed and test the legibility of nine different expressive motions in an online user study with 98 participants. We found several differences between the motions in communicating messages to the users. These findings represent a promising starting point for the design of legible expressive motions for implementation in decentralized robot swarms.
In this paper, we study the problem of mobile entities that synchronously have to explore and repair a graph with faulty nodes, usually called black-holes, that destroy any entering entity. We consider the scenario wh...
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In this paper, we study the problem of mobile entities that synchronously have to explore and repair a graph with faulty nodes, usually called black-holes, that destroy any entering entity. We consider the scenario where the destruction of an entity by means of a black-hole also affects all the entities within a fixed range r (in terms of number of edges), while the black-hole disappears. Clearly, if there are b black-holes in the graph, then k >= b entities are necessary to remove all of them from that graph. We ask for the minimum number of synchronous steps needed to make safe all the graph. The results of this paper are both theoretical and experimental, and can be summarized as follows. From the theoretical point of view, first we show that the problem is NP-hard even for b = k = 1. Then, we provide a general lower bound holding when r >= 0 and a higher one for the case of r > 0. We then consider the case of r <= 1. We propose an optimal solution holding when k is unbounded, that is, an infinite number of robots is available. Then, we provide three different exploration strategies, named snake, scout, and parallel-scout, respectively, for the case of bounded k, that is, the number of robots is fixed a priori. The three strategies are then analyzed according to the time complexity with respect to the lower bound. From the experimental point of view, we implemented the three strategies and tested them on different scenarios with the aim of assessing their practical performance. The experiments confirm the theoretical analysis and show that parallel-scout is always by far the best exploration strategy in practice. (C) 2015 Elsevier B.V. All rights reserved.
This work aims at proposing a method for building a map of a priori percentage density of expected findings over an area from historical qualitative information and at defining a cooperative distributed exploration al...
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Searching algorithms and path planning algorithms are in a variety of applications, where the mobile robotics field is one of the most popular. QPA* algorithm attempts to perform this two strategies at the "same ...
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ISBN:
(纸本)9781728195940
Searching algorithms and path planning algorithms are in a variety of applications, where the mobile robotics field is one of the most popular. QPA* algorithm attempts to perform this two strategies at the "same time". The algorithm makes use of three strategies to generate a different solution to the exploration and path planning mainstream, using a "proposed version" of a modified A* (star) algorithm, the idea of the Potential Fields Algorithm (to deal with the collision avoidance) applied as a artificial binary field, and an exploration heuristic named "quadrant grid search". The QPA* algorithm is designed to be applied in a search and rescue robot, where the problem of "localization" and "mapping" is consider to be independent of the exploring and path planning algorithm. The "exploration" part of QPA * is intended to overcome the main problem of path planning algorithms, that is the lack of a true "exploration factor" and preserve the efficiency of making a route using the path planning approach of A* algorithm. Finally, we test three different approximations (for the path planning part) in combination with the quadrant grid search, in order to identify the pros and cons of this design.
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