Abstract
Robot area exploration is a very important task in robotics because it has many applications in real-life problem. So, this is always a very interesting field for researches. This paper presents a new method for multi-robot area exploration. Here, first the environment is divided into partition. In each partition, the robot is deployed randomly. Each partition is explored separately by robot. For the movement of robots, well-known particle swarm optimization algorithm is used. Here mainly concentrated on the multi-robot-coordinated exploration for unknown search spaces where decisions made by bio-inspired algorithms for movement and thus helping in exploration. For better and fast exploration, robot should be scattered in different directions; for this purpose, new clustering-based distribution method is used. The proposed method is tested on different simulated environments that are considered as indoor and outdoor environments. Different parameters such as move, coverage, energy, and time are calculated. The results show that method works well for both environments.
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Sharma, S., Sur, C., Shukla, A., Tiwari, R. (2015). Multi-robot Area Exploration Using Particle Swarm Optimization with the Help of CBDF-based Robot Scattering. In: Sethi, I. (eds) Computational Vision and Robotics. Advances in Intelligent Systems and Computing, vol 332. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2196-8_14
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DOI: https://doi.org/10.1007/978-81-322-2196-8_14
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