一种融合行人预测信息的局部路径规划算法

A Local Path Planning Algorithm Based on Pedestrian Prediction Information

  • 摘要: 随着机器人技术的不断发展与实践,大量的服务机器人出现在商场、学校、医院以及餐厅等人流量较大的应用场景中。行人在接打电话或使用手机时,难以细致观察周围路况,易与运动中的机器人发生擦碰,因此高动态的工作环境对机器人运动规划提出了较高的要求。为了提高机器人在高动态复杂场景中的运动能力和智能化水平,提出了一种融合行人预测信息的局部路径规划算法。该算法以行人相对于机器人的位置和速度作为先验输入信息,创新性地提出了随机器人与行人速度动态变化的组合椭圆行人区域概念,通过对经典动态窗口法中的评分函数进行扩展,实现机器人对行人的智能避让,最大程度地降低因机器人移动对行人原始行动意图造成的干扰。实验证明,该算法可以有效降低机器人与行人发生擦碰的风险,能够在不干扰行人运动的情况下提前做出预判并实现智能绕行。

     

    Abstract: With the continuous development and practice of robotics, a large number of service robots have appeared in the areas with large human flows, such as shopping malls, schools, hospitals, and restaurants. Many people make calls or operate mobile phones while walking, but fail to observe the surroundings carefully, thus they are prone to be collided with the moving robots. Therefore, the motion planning of the robot is subject to higher requirements by the highly dynamic environment. In order to improve the robot's mobility and intelligence, a local path planning algorithm based on pedestrian prediction is proposed in the paper. The position and speed of pedestrians relative to the robot is taken as the priori input of the algorithm, and the concept of an elliptical pedestrian zone which dynamically changes with the speed between the robot and the pedestrian is innovatively proposed. By extending the scoring function of the classic dynamic window approach, the robot's intelligent avoidance of pedestrians is achieved, and the interference caused by robot movements on pedestrians' moving intentions is minimized. The experimental results show that the algorithm can effectively reduce the risk of the collision between robot and pedestrian, and can make a pre-judgment and intelligent avoidance without the attention of the pedestrian.

     

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