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In security defense tasks, multiple robots need work cooperatively to detect offensive intrusion to protect some sensitive areas. In this paper, we propose a distributed algorithm for a multi-robot system with some static sensors. The system concept is that static sensors sense intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the potential intruder, performing...
Inspired by the major principles of gene regulation and cellular interactions in multi-cellular development, this paper proposes a distributed self-organizing algorithm for multi-robot shape formation. In this approach, multiple robots are able to self-organize themselves into complex shapes driven by the dynamics of a gene regulatory network model. Particularly, no predefined global coordinate system...
Morphogenesis is the biological process that governs self-organized spatial pattern formation of cells during the embryonic development of multi-cellular organisms. Inspired by this process, we have proposed a morphogenetic framework for pattern formation and boundary coverage in a distributed swarm robotic system. The framework is based only on local communications among robots and will set up a...
Biological systems can generate robust and complex behaviors through limited local interactions in the presence of large amount of uncertainties. Inspired by biological organisms, we have proposed a gene regulatory network (GRN) based algorithm for self-organizing multiple robots into different shapes. The self-organization process is optimized using a genetic algorithm. This paper focuses on the...
In this paper, we propose an autonomous system consisting of cooperative mobile robots and fiber optic sensors (FSs) for intruder detection in perimeter defense tasks. The system concept is that FSs will sense perimeter intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the potential intruder, performing surveillance and/or neutralization of the intrusion....
Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, infinite richness, and limited availability of information. Gene regulatory networks (GRNs) are models of genes and gene interactions at the expression level. In this paper, inspired by the biological organisms and GRNs models, a distributed multi-robot self-construction method is...
A collective construction task require a multi-robot system to search for randomly distributed building blocks and push those blocks to some predefined locations. To address this problem, a bio-inspired swarm intelligence based algorithm is proposed for a distributed multi-robot system to combine explorative searching and dynamic task allocation together for collective construction. Basically, a virtual...
Miniature robots have many advantages over their larger counterparts, such as low cost, low power, and easy to build a large scale team for complex tasks. Heterogeneous multi miniature robots could provide powerful situation awareness capability due to different locomotion capabilities and sensor information. However, it would be expensive and time consuming to develop specific embedded system for...
Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selections, and difficulty in merging learned experiences from other robots. In this paper, we propose a dynamic correlation matrix based multi-Q learning (DCM-MultiQ) method for a distributed multi-robot system. A novel dynamic correlation...
Some common issues exist in the bio-inspired algorithms for a multi-robot system include considerable randomness of the robot movement during coordination and unevenly distributed robots in a multi-task environment. To address these issues, a self-adaptive distributed multi-task allocation method in a multi-robot system is proposed in this paper. In this method, each robot only communicates with its...
Distributed coordination is critical for a multi-robot system in hazardous waste cleanup under a dynamic environment. To achieve higher efficiency as well as robustness, a bio-inspired local interaction via virtual stigmergy (LIVS) coordination approach is proposed in this paper. This new meta-heuristic integrates two mechanisms - stigmergy-based autocatalytic mechanism and particle swarm optimization...
In this paper, a communication-efficient dynamic task scheduling algorithm for a heterogeneous multi-robot system is proposed. To make this task scheduling algorithm to be scalable for various robot teams, a distributed communication with shared global unit mechanism is applied to reduce the storage cost as well as communication overhead. Each robot makes its own decision through communicating with...
The limited power, low radio range, and an ever changing environment make the ability to explicitly communicate between multi-robots decreases in a searching task. When this happens, maintaining the weakened connection will cause robots to cluster during searching, which may be suboptimal with respect to the searching time. In this paper, several integration strategies are proposed to coordinate a...
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