Multi-robot Automated Search for Non-Adversarial Moving Evaders in an Unknown Environment

In this paper, the problem of searching for moving evaders in unknown environment using group of mobile robots is investigated. The aim is to find the moving evaders as fast as possible. Three different search techniques are proposed and evaluated through extensive experimentation. In the first two techniques, robots do not cooperate or coordinate their actions. Alternatively, they implement simple movement strategies to locate the evaders. On the contrary, in the third technique, robots employ explicit coordination among each other and they implement a relatively complex algorithm based on voronio graph to find the evaders. In the later technique, each robot needs to be equipped with communication and localization capabilities. The results showed that graph-based technique led to shortest search time. However, it also showed that a reasonable performance is possible with cheap robots implementing simple and non-coordination techniques. Keywords: Search, Multi-Robot, Voronio Graph, Moving Target, Coordination

A New Frontier Based Approach for Multi-Robot Coverage in Unknown Environments

With the emergence of technology in our daily lives, robots are being increasingly used for coverage tasks which were earlier considered too dangerous or monotonous to be performed by humans such as interplanetary exploration and search & rescue. Out of all the multi-robot coverage approaches, the frontier based approach is one of the most widely used. Most of the coverage approaches developed so far, face the issue of frontier duplication and require access to the maps of the environment prior to coverage. In this work, we have developed a new frontier based approach for multi-robot coverage in unknown environments. This new approach is scalable to multiple robots and does not require prior access to the maps. This approach also uses a new frontier allocation and robot coordination algorithm, which reduces the frontier duplication in the robots and improves the efficiency of robot coverage

Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots

Safe robot navigation is a fundamental research field for autonomous robots including ground mobile robots and flying robots. The primary objective of a safe robot navigation algorithm is to guide an autonomous robot from its initial position to a target or along a desired path with obstacle avoidance. With the development of information technology and sensor technology, the implementations combining robotics with sensor network are focused on in the recent researches. One of the relevant implementations is the sensor network based robot navigation. Moreover, another important navigation problem of robotics is safe area search and map building. In this report, a global collision-free path planning algorithm for ground mobile robots in dynamic environments is presented firstly. Considering the advantages of sensor network, the presented path planning algorithm is developed to a sensor network based navigation algorithm for ground mobile robots. The 2D range finder sensor network is used in the presented method to detect static and dynamic obstacles. The sensor network can guide each ground mobile robot in the detected safe area to the target. Furthermore, the presented navigation algorithm is extended into 3D environments. With the measurements of the sensor network, any flying robot in the workspace is navigated by the presented algorithm from the initial position to the target. Moreover, in this report, another navigation problem, safe area search and map building for ground mobile robot, is studied and two algorithms are presented. In the first presented method, we consider a ground mobile robot equipped with a 2D range finder sensor searching a bounded 2D area without any collision and building a complete 2D map of the area. Furthermore, the first presented map building algorithm is extended to another algorithm for 3D map building