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1、1A Matlab-based Simulator for Autonomous Mobile Robots AbstractMatlab is a powerful software development tool and can dramatically reduce the programming workload during the period of algorithm development and theory research. Unfortunately, most of commercial robot simulators do not support Matlab.
2、 This paper presents a Matlab-based simulator for algorithm development of 2D indoor robot navigation. It provides a simple user interface for constructing robot models and indoor environment models, including visual observations for the algorithms to be tested. Experimental results are presented to
3、 show the feasibility and performance of the proposed simulator. Keywords: Mobile robot, Navigation, Simulator, Matlab 1. Introduction Navigation is the essential ability that a mobile robot. During the development of new navigation algorithms, it is necessary to test them in simulated robots and en
4、vironments before the testing on real robots and the real world. This is because (i) the prices of robots are expansive; (ii) the untested algorithm may damage the robot during the experiment; (iii) difficulties on the construction and alternation of system models under noise background; (iv) the tr
5、ansient state is difficult to track precisely; and (v) the measurements to the external beacons are hidden during the experiment, but this information is often helpful for debugging and updating the algorithms. The software simulator could be a good solution for these problems. A good simulator coul
6、d provide many different environments to help the researchers to find out problems in their algorithms in different kinds of mobile robots. In order to solve the problems listed above, this simulator is supposed to be able to monitor system states closely. It also should have flexible and friendly u
7、sers interface to develop all kinds of algorithms. Up to now, many commercial simulators with good performance have been developed. For instance, MOBOTSIM is a 2D simulator for windows, which provides a graphic interface to build environments 1. But it only supports limited robot models (differentia
8、l driven robots with distance sensors only), and is unable to deal with on visual based algorithms. Bugworks is a very simple simulator providing drag-and-place interface 2; but it provides very primitive functions and is more like a demonstration rather than a simulator. Some other robot simulators
9、, such as Ropsim 3, ThreeDimSim 5, and RPG Kinematix 6, are not specially designed for the development of autonomous navigation algorithms of mobile robots and have very limited functions. 2Among all the commercial simulators, Webot from Cyberbotics 4 and MRS from Microsoft are powerful and better p
10、erformed simulators for mobile robot navigation. Both simulators, i.e. Webots and MRS, provide powerful interfaces to build mobile robots and environments, excellent 3-D display, accurate performance simulation, and programming languages for robot control. Perhaps due to the powerful functions, they
11、 are difficult to use for a new user. For instance, it is quite a boring job to build an environment for visual utilities, which involves shapes building, materials selection, and illumination design. Moreover, some robot development kits have built-in simulator for some special kinds of robots. Ari
12、a from Activmedia has a 2-D indoor simulator for Pioneer mobile robots 8. The simulator adopts feasible text files to configure the environment, but only support limited robot models. However, the majority of commercial simulators are not currently supporting On the other hand, Matlab programming th
13、at provides a good support in matrix computing, image processing, fuzzy logic, neural network, etc., and can dramatically reduce the coding time in the research stage of new navigation algorithms. For example, a matrix inverse operation may needs a function which has hundreds of lines; but there is
14、a simple command in Matlab. To use Matlab in this stage can avoid time-wasting on regenerating existed algorithms repeatedly and focus on the new theory and algorithm development. This paper presents a Matlab-based simulator that is fully compatible with Matlab codes, and makes it possible for robot
15、ics researchers to debug their code and do experiments conveniently at the first stage of their research. The algorithms development is based on Matlab subroutines with appointed parameter variables, which are stored in a file to be accessed by the simulator. Using this simulator, we can build the e
16、nvironment, select parameters, build subroutines and display outputs on the screen. Data are recorded during the whole procedure; some basic analyses are also performed. The rest of the paper is organized as follows. The software structure of the proposed simulator is explained in Section II. Section III describes the user interface of the proposed simulator. Some experimental results are given in Section IV to show the system performance. Finally, Section V presents
