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Real-time and accurate robot detection and localization is important for the RoboCup Middle size League (MSL) soccer robots. In the current robot detection methods used by most of the teams, the black-color-based information is used to distinguish robots from the environment, which is not robust if the robot changes its makers' color according to the current rule. Considering the good performance...
Encirclement control enables a multi-robot system to rotate around a target while they still preserve a circle formation, which is useful in real world applications such as entrapping a hostile target. In this paper, a distributed control law is proposed for any number of anonymous and oblivious robots in random three dimensional positions to form a specified circular formation with any desired inter-robot...
In RoboCup middle size league (MSL), the basic purpose for the soccer robots is to realize obstacle avoidance and shooting without stop by utilizing trajectory planning to provide a smooth trajectory. Consider the highly competitive and highly dynamic match environment, in fact, the trajectory planning is very challenge. The implementation for mobile robots generating trajectory is complex in a highly...
In dynamic environments, mobile robots sometimes are required to perform accurate and stable tracking of high-speed trajectories, but rare researches are reported, which specifically deal with high-speed tracking problem. When tracking high-speed trajectories, mobile robots usually approach the top speed and acceleration limits, which indicates that the kinematic constraints can not be ignored. In...
Recognizing the FIFA ball without color classification is a significant ability for robocup middle size league soccer robots to play competition without the constraint of current color-coded environment. This paper describes a novel method to recognize the ball based on omni-directional vision system and perspective camera without color classification. Firstly the imaging character of the omni-directional...
One of the challenges of SLAM (simultaneous localization and mapping) for autonomous robots is the loop closing problem. In this paper, a decision-theoretic active loop closing approach is presented, which integrates the exploration planning with loop closing. In our approach, the active loop closing process is modeled as a multi-stage decision problem, and a frontier-based auxiliary topological map...
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