针对移动机器人在未知环境中探测和规避障碍物困难等问题,提出一种基于椭圆建模和自然语言处理(nataral language processing,NLP)算法的移动机器人路径规划方法。首先将激光采集的点信息进行分类和最小椭圆包围,建立障碍物的椭圆模型并估算出障碍物的速度。然后采用NLP算法,把移动机器人在未知环境中的路径规划问题,描述成了满足一组非线性约束和目标函数最小的非线性规划问题,从而实现复杂未知环境下机器人的路径规划。最后进行物理与仿真实验,验证了该方法的有效性。
Aim atrobot obstacle inaccurate detection and avoidance difficulty problems in unknown environment, a novel algorithm based on elliptic model and NLP algorithm is proposed for robot path planning. First, point information is categorized from laser collection and surrounding it by minimum ellipse, building elliptic model for obstacles and estimating its velocity. Then, so as to realize robot path planning in complex unknown environment, the path planning problem is described as nonlinear programming problems which satisfy a set of nonlinear constraints and minimum objective function. The physics and simulation results verify the effectiveness of the proposed method.