Distance Measurement for Indoor Robotic Collectives [chapter]

Mihai V., Andrei Stancovici, Sinziana Indreic
2011 Mobile Robots - Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator Training  
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,
more » ... nder 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-of-Flight) 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. Current techniques for robot distance estimation The problem of inter-robot distance measurement and location monitoring is considered of key importance in the field and, consequently, a large number and variety of methods have been proposed and studied in the literature. For instance, the GPS system (Ohno et al., 2004; Reina et al., 2007) and landmark-based solutions such as the Cricket Indoor Location System (Cricket Project, 2005; Priyantha, 2005) are well established in the field. On the other hand, www.intechopen.com Mobile Robots -Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator Training 354 they do not comply with the constraints specified in the previous section (i.e. independence of fixed landmarks). In this section we discuss some of the most prominent techniques which can be used for indoor robotic collectives. Time-Difference-of-Arrival (TDOA) measures the distance between two points by using two different types of signals (usually radio and acoustic) which cover the route connecting the two points with different speeds. To illustrate this technique, consider two points, A and B, located at distance d from each other. At a time instance, the transmitter from A sends simultaneously the signals S 1 and S 2 , which cover the distance d at the speeds v S1 and v S2 , respectively. If, for example, v S2 < v S1 , then signal S 2 arrives at the receiver B after S 1 , with a delay which depends on the distance d. This delay is measured at the destination point B and the value of d is consequently derived. Cricket Indoor Location System uses TDOA to measure the distance to the reference points. The system consists of several landmark transmission devices, depending on the size of the desired coverage area (at least three modules) and one or more mobile devices that play the role of receptors. In most cases, the transmission devices are attached to the upper part of the room so as to cover a large portion or the entire room. The reception devices are attached to robots, located on the floor. As shown in (Priyantha, 2005) , the system relies on two types of signals to calculate distances: a RF (radio) signal and an ultrasonic signal. The radio signal is 10 6 times faster than the ultrasonic signal, and the distance is calculated by applying the principle of TDOA to the difference of the two propagation periods. The localization of mobile robots through this system is made at an accuracy of 1 ÷ 3 cm. Similarly, the system presented in (Fayli & Kleeman, 2004) solves the localization problem based on four transmitters as fixed reference points and a wireless receiver. Another well known technology used in robotics to calculate distance is based on infrared (IR) sensors. There are several types of IR sensors, each varying according to their parameters (e.g. maximum range and accuracy) and price. In comparison to ultrasonic devices, the IR sensors are cheaper and use light, which is much faster than the acoustic signal. They have nonlinear characteristics which depend on the surface reflectance of the objects. Based on measuring the intensity of light reflected by a target, the IR sensors can calculate the distance to it. This technique is presented and discussed in several works, including (Novotny & Ferrier, 1999; Ha & Kim, 2004; Mohammad, 2009 ). Hagisonic StarGazer (Hagisonic, 2009) is a location system for mobile robots, based on the analysis of infrared rays which are reflected by a passive landmark with a unique ID. The system works as follows: 1. The IR transmitter is located on the robot. It transmits infrared beams to the fixed landmark attached to the ceiling of the room. 2. The infrared rays are reflected from the landmark and reach the Stargazer, mounted on the robot. 3. Stargazer contains a CMOS camera able to estimate the angle of incidence of the reflected IR waves and the distance between the robot and the landmark. 4. Based on the angle of incidence and on the distance to the landmark, the position of the robot in the room can then be obtained through geometric techniques. The advantage of such a system is its accuracy, which, according to (Hagisonic, 2009) , can reach approximately 2 cm. The system can carry out 20 measurements per second. Its disadvantage is the high price and the reduced coverage area, which ranges from 2.5 to 5 m. A set of radio-based methods use the power of the received signal to estimate the distance to the source. The mathematical model of the emitted signal power is given in (Fuicu et al.,
doi:10.5772/25810 fatcat:5whrl73llrf7phh24we3iacw54