Communication model and Optical Flow to Aid Collaborative Robotics Search Strategy

Abstract

This thesis provides an analysis of how communication among robots improves search performance in a multi-robot search and rescue scenario. Mobility models have been used to represent the movement patterns in vehicular and mobile ad-hoc networks. As more and more collaborative robotics applications employ the use of these models, there is a need for them to be better suited for practical applications, and communications is imperative for these operations. Along with exploring the advantages of communications between the mobile robots, this thesis also gives an overview of an optical flow algorithm to aid in robot navigation. This algorithm was designed to be used in a busy environment which holds a lot of moving obstacles. The traditional mobility models have been changed a little with the inclusion of obstacles to suit the experiments and need of collaborative robotics applications. The key results of this thesis are that incorporating communications between the robots reduces the time taken for target detection by a considerable value. The results also explore the change in the time taken to reach the target with change in a set of parameters, like the number robots, number of obstacles, sensor range.The results of the optical flow process show a disparity map generated by the robot, which helps it in analyzing the environment it is a part of, and decide its next move accordingly.