Distance Measurement for Indoor Robotic Collectives

Abstract

Location monitoring is a common problem for many mobile robotic applications covering various domains, such as industrial automation, manipulation in difficult areas, rescue operations, environment exploration and monitoring, smart environments and buildings, robotic home appliances, space exploration and probing. A key aspect of localization is inter-robot distance measurement. In this chapter we consider the problem of autonomous, collaborative distance measurement in mobile robotic systems, under the following set of design and functional constraints: a. indoor operation, b. independence of fixed landmarks, c. robustness and accuracy, d. energy efficiency, e. low cost and complexity. This work significantly extends and updates the results previously published in (Micea et al., 2010). We present and discuss some of the most relevant state of the art techniques for robot distance estimation. Next, we introduce a framework for collaborative inter-robot distance measurement along with a procedure for accurate robotic alignment. The proposed alignment algorithm is based on evaluating and comparing the strength of ultrasonic signals at different angles, processing (filtering) the measured data and ensuring a good synchronization during the process. Further on, we present the CTOF (Combined Time-ofFlight) method for distance measurement, which brings significant improvements to the classical TOF technique, and we show how this new technique meets the above specified design constraints. Some of the most interesting test and evaluation results are presented and discussed. The experimental data show how the distance estimation accuracy can be increased by applying the Kalman filter algorithm on repetitive measurements. The final remarks and the reference list conclude this chapter.