Simultaneous Localization of Robots and Mapping of Wireless Sensor NodesCooperative Robots and Sensor Networks 2014

This chapter presents the use of a mobile robot to solve the problem of node localization in Wireless Sensor Network (WSN). The algorithms we propose are inspired by the algorithms developed in robotics to solve the robot localization problem exploiting landmarks in the environment. The robotics community developed algorithms of Simultaneous Localization and Mapping (SLAM), in which the robot pose is estimated while simultaneously mapping the position of the landmarks in the environment. Similarly, we simultaneously estimate the robot pose with the position of the nodes of a WSN using range measurements. The assumption is that a mobile robot can estimate the distance to nearby nodes of the WSN by measuring the Radio Signal Strenght (RSS) of the received radio messages. The intrinsic variability of RSS measurements due to interferences and reflections of radio signals, however, makes the ranging measure very noisy, thus limiting the accuracy of simple localization techniques. We first present a SLAM technique based on an Extended Kalman Filter (EKF-SLAM) to integrate RSS measurements from the different nodes over time, while the robot moves in the environment. Successively, we show that combining the EKF-SLAM algorithm with an initialization phase based on a Delayed Particle Filter (DPF) can greatly improve the performance of the algorithm. We then discuss possible extensions of the approach by using advanced RSS measurement techniques, and multidimensional scaling localization. Finally, we compare the different approaches on the same experimental testbed, both for indoor and outdoor scenarios

Are middlewares ready for multi-robots systems?

International audienceAutonomous robot fleets are complex systems that require the interaction and communication between heterogeneous hardware and software. Despite many years of work in robotics, there is still a lack of established software architecture and middleware, in particular for large scale multi-robots systems. Many research teams are still writing specific hardware orientated software that is very tied to a robot. This vision makes sharing modules or extending existing code difficult. A robotic middleware should be designed to abstract the low-level hardware architecture, facilitate communication and integration of new software. In this paper, we present and compare seven existing middlewares capable of being used in multi-robot systems. We also present two dedicated cloud based multi-robots platforms. After this analysis, we discuss why a cloud of robots and not a cloud for robots is more suitable in a fleet context