煤矿井下移动机器人运动规划方法研究

Research on motion planning method of underground mobile robot

  • 摘要: 针对现有煤矿井下移动机器人运动规划所生成的轨迹存在超调、碰撞、不连续、不光滑等问题,提出了一种由路径规划、轨迹生成、轨迹优化3个部分构成的煤矿井下移动机器人运动规划方法。路径规划采用基于图搜索的A*算法实现,通过开始搜索、路径排序、继续搜索3个步骤循环迭代,快速规划出一条可通行的全局路径作为轨迹生成的初值。轨迹生成通过构建基于Minimum Snap的目标函数,并施加等式约束来实现。轨迹优化则是在轨迹生成的基础上施加不等式约束来实现:通过调整时间分配和构建基于Corridor轨迹规划的不等式约束,解决基于Minimum Snap轨迹生成在求解过程中出现的超调现象,并对整段轨迹本身进行约束,避免发生碰撞;通过引入调和函数Bezier Curve,构建基于Bezier Curve的Minimum Snap的轨迹优化问题,使得轨迹高阶目标函数的求解变得简单高效,最终生成一条适用于煤矿井下移动机器人的能量损失最小、连续、光滑、无碰撞、可执行的运动轨迹。在Matlab仿真环境中设计了随机地图,生成了包含时间分配、位置规划、速度规划、加速度规划的最优轨迹规划结果。实验结果验证了该运动规划方法的正确性和有效性。

     

    Abstract: In view of problems of overshoot, collision, discontinuity and unsmoothness in the trajectory generated by motion planning of existing underground mobile robot, a motion planning method of underground mobile robot was proposed, which consists of path planning, trajectory generation and trajectory optimization. Path planning is realized by A* algorithm based on graph search, and a passable global path is quickly planned as initial value of path generation through three steps of cycle iteration, namely start search, path sorting and continue search. Trajectory generation is realized by constructing objective function based on Minimum Snap and applying equality constraint.Trajectory optimization is achieved by applying inequality constraints on the basis of trajectory generation: by adjusting time allocation and building inequality constraints on Corridor trajectory planning, the overshoot phenomenon that occurs during solution process for Minimum Snap trajectory generation is resolved and the entire trajectory itself is constrained to avoid collisions; by introducing the harmonic function Bezier Curve, the trajectory optimization problem of the Minimum Snap based on Bezier Curve is constructed, which makes the solution of the high-order objective function simple and efficient, and finally generates a motion trajectory which is suitable for the underground mobile robot with minimum energy loss, continuous, smooth, collision free and executable.In the Matlab simulation environment, the random map is designed, and the optimal trajectory planning results including time allocation, location planning, speed planning and acceleration planning are generated.The experimental results verify the correctness and effectiveness of the motion planning method.

     

/

返回文章
返回