Among the study of robotic, multi-robot research has become a hot trend, multi-robot cooperation can solve many problems that single robot can not solve. In multi-robot system, collaboration localization is the key technology to determine the system performance. Multi-sensor collaboration localization can overcome problems like accumulative error, Low measurement precision that single sensor may have. Outdoor robots formation enables the robot to effectively complete the tracking, investigation and other tasks. It has great practical significance to do robot dynamic formation based on collaboration localization and invest wild terrain adaptation strategy. This paper basically has two parts. The first part use multi-sensor to do collaboration localization, and the second part mainly talk about the robot dynamic formation based on collaboration localization and also the wild terrain adaptation strategy. Firstly, in purpose to get precise position of robot using multi-sensor, a joint filter model is constructed which has three sub-filters and a main filter. The first sub-filter use the discrete Kalman filter to fusion the information from photoelectric encoder and gyro, then the Inertial Navigation System model is derived. The output of the first sub-filter is then used as the control input of the other two sub-filters, and the other two sub-sensors fusion the information of Inertial Navigation System with ultrasonic sensors and GPS respectively. The second sub-filter use Relative observation between two robots as observation information, extend Kalman filter can be used to correct the relative position of the two robots. The third sub-sensor use GPS information as observation information, extended Kalman filter can eliminate the accumulated error generated by the Inertial Navigation System. At last, the main filter fusion the information from the last two sub-filter. Secondly, with the basics of robot positioning using collaboration localization, this paper proposes a method for UGV(Unmanned Ground Vehicle) team-formation remain and a controlling strategy in the uncertain outdoor environment. A navigation strategy based on obstacle classification is used. The strategy use an algorithm to decide whether the obstacle detected by laser sensor can be passed through or not, and a formation strategy using the artificial potential field method is proposed based on this. Finally, a Summary and Outlook for cooperative localization multi-UGV formation control is ...
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