穿越稠密障碍物的自适应动态窗口法

针对应用广泛的局部避障算法-----动态窗口法(DWA)穿越稠密障碍物时存在路径不合理、速度和安全性不能兼顾等问题,提出参数自适应的DWA算法,根据机器人与障碍物距离和障碍物的密集度自动调整目标函数中的权值,以自适应环境的动态变化,从而获得移动机器人的最佳运行速度和合理路径.该方法可明显改善机器人穿越稠密障碍物区域时的性能;同时,该方法还可避免机器人从密集障碍物区域外绕行以及轨迹不平滑现象.仿真实验表明:改进的DWA算法在复杂环境中通过逐步优化可使运行轨迹更加合理,能够同时兼顾路径平滑性和安全性;机器人在离稠密障碍物较远处保持高速,通过狭窄通道或者稠密障碍物区域时速度适当降低,安全性更高,实验中总迭代次数和运行时间可缩短20%以上.

Self-adaptive dynamic window approach in dense obstacles

Dynamic window approaches(DWAs) are widely used in local obstacle avoidance of mobile robots. A self-adaptive DWA algorithm is proposed for the problem that the classical DWA exists unreasonable path in dense obstacles and it cannot ensure both speed and security. In order to adapt to the dynamic environment, the weight of speed in the target function is adjusted automatically based on the distance and orientation between the robot and obstacles. The optimal velocity and reasonable planned path of the mobile robot are obtained using the self-adaptive DWA. Thus the performance of the robot crossing an area of dense obstacle is significantly improved. The problems that the robot might move around the dense obstacles and result in an unsmooth path are solved. Our experiments show that the proposed algorithm can make running track more reasonable through gradual optimization in the complex environment than old one, and it ensures the smoothness and security of robot route simultaneously. When the robot is far from the dense obstacles, the robot keeps high speed. When the robot passes through a narrow passage or a dense obstacle area, the speed appropriately reduces and the safety grows high. The total number of iterations and the run-time can be reduced more than 20% in our experiments.