Multi – Robot Exploration Supported by Enhanced Localization with Reduction of Localization Error Using Particle Swarm Optimization
M. RajeshDepartment of Computer Science and Engineering, Amrita School of Computing, Bengaluru, Amrita Vishwa Vidyapeetham, India. m_rajesh@blr.amrita.edu0000-0001-6949-211X
S.R. NagarajaDepartment of Aerospace Engineering, Dayanand Sagara University, Bengaluru, India. nagaraja@dsu.edu.in0000-0003-0718-6963
P. SujaDepartment of Computer Science and Engineering, Amrita School of Computing, Bengaluru, Amrita Vishwa Vidyapeetham, India. p_suja@blr.amrita.edu0000-0001-8252-5828
Exploration of an area by a group of robots is an active research field of robotics as multi-robot exploration is applied extensively in several real life scenarios. The major challenges in such exploration are the availability of communication infrastructure as communication plays a key role in the coordination of team of robots for effective coverage of the area under exploration. But in disaster affected scenarios, there will be no existing communication infrastructure available and this makes the exploration ineffective and time consuming. Another challenge is in the localization process each robot is carrying out to update the map as well as for exchange of information with other robots. In this paper, an enhanced Multi-robot exploration strategy is introduced. The base of the exploration strategy is two techniques. The first one being localization of each robot involved in the exploration and this is done with the help of trilateration where three anchors are required which will be setup before the exploration starts. The second part is navigation and avoiding overlapping or missing out sectors while exploring. This is done with help of a navigation policy called frontier cell based approach. Further to this, the exploration strategy is supported with localization error reduction scheme in which the localization error is reduced with the help of Particle Swarm Optimization (PSO). The entire scheme is simulated and exploration time is analyzed for the same environment in different obstacle density and different number of robots to perform exploration. The results show the scheme is better than many existing multi-robot exploration strategies. Precisely, the proposed scheme is able to reduce the localization error to a threshold level of 0.02cm or below which can be considered as novel contribution towards the exploration strategies.