| Main effect of Coal Mine Detection Robot is taking place of human to go into the post-disaster coal mine for detecting information of the environment and sending the information to the command center. Therefore, it is of great significance to research on Coal Mine Detection Robot for reducing casualties and unfolding of the saving work smoothly. The issue of"Research on technologies and systems of coal mine rescue and detection robot"is scientific and technological project in Shanxi Province. Researches on path planning and motion control are not only the key technologies of the issue but also the guarantee on completing the detection task of Coal Mine Detection Robot.Main work of path planning for Coal Mine Detection Robot are not only to find a safe and collision-free path from the starting point to end point in the environment of post-disaster coal mine with the uncertain obstacles in it but also to make the path shorter and energy consumed less. Firstly, in this paper, grid-based method is used in robot local environmental modeling. Secondly, because the exist of disadvantage of standard Particle Swarm Optimization is easy to fall into local optimality. Particle Swarm Optimization is improved by random initialization of the particles again. And simulation results show the feasibility of the algorithm. Thirdly, basing on the research on the Particle Swarm Optimization, a path planning method of the Coal Mine Detection Robot is propounded which base on Behavior and Particle Swarm Optimization. Behavior of the Robot's path planning is decomposed into Trending To Target behavior and Obstacle Avoidance behavior according to the Behavior. Robot's current behavior is established by information of obstacle in the rolling scan region. And the method of path planning take into account the global optimality at the same time of ensuring the local optimality by applying to the method of establishing the sub-goals with taking into account the overall situation. At last, validate the effectiveness of the algorithm by simulation of the Path Planning algorithm base on Behavior and Particle Swarm Optimization in MATLAB.According to mechanism's characteristics of Coal Mine Detection Robot, the body of motion control is divided into Master Module and Rocker Arm Module. Firstly, the kinematics equations of Master Module and the formula of speed on going straight and turning are derived according to the kinematics equations of wheeled mobile robot. Secondly, the kinematics equations of Rocker Arm Module are derived according to simplifying the robot's rocker arms as open chain mechanisms of space connecting rod. Thirdly, hardware system and software system of Motion Control are selected and designed. According to debugging the windows of"Path Dynamic Display"and"Images Capture"successfully, robot's reasonable path, obstacles'information and environmental information in coal mine are viewed immediately, and it is the foundation of remote monitoring and remote control. At last, kinematics simulation model of Coal Mine Detection Robot is established by applying to software of Pro-Engineer, and the kinematics equations of Master Module are simulated by applying to software of ADAMS successfully. They not only testify to the valid of the kinematics equations but also the feasibility of the path planned. |
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