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

RSSI-based localization of a wireless sensor node with a flying robot

We consider the problem of navigating a ying robot to a specific sensor node within a wireless sensor network. This target sensor node periodically sends out beacons. The robot is capable of sensing the received signal strength of each received beacon (RSSI measurements). Existing approaches for solving the sensor spotting problem with RSSI measurements do not deal with noisy channel conditions and/or heavily depend on additional hardware capabilities. In this work we reduce RSSI uctuations due to noise by continuously sampling RSSI values and maintaining an exponential moving average (EMA). The EMA values enable us to detect significant decrease of the received signal strength. In this case it is reasoned that the robot is moving away from the sensor. We present two basic variants to decide a new moving direction when the robot moves away from the sensor. Our simulations show that our approaches outperform competing algorithms in terms of success rate and ight time. Infield experiments with real hardware, a ying robocopter successfully and quickly landed near a sensor placed in an outdoor test environment. Traces show robustness to additional environmental factors not accounted for in our simulations