快速扩展随机树算法(rapidly-exploring random trees,RRT)规划移动机器人路径时,存在搜索盲目性强、搜索时间长、收敛速度慢、路径冗余点多且不平滑等问题。鉴于此,提出一种改进的RRT路径规划算法。首先,针对传统RRT算法盲目搜索以及...快速扩展随机树算法(rapidly-exploring random trees,RRT)规划移动机器人路径时,存在搜索盲目性强、搜索时间长、收敛速度慢、路径冗余点多且不平滑等问题。鉴于此,提出一种改进的RRT路径规划算法。首先,针对传统RRT算法盲目搜索以及局部极值的问题,提出概率目标偏置与人工势场结合的采样策略,引导随机树的扩展;其次,针对随机树扩展的避障能力差的问题,提出基于安全距离的碰撞检测以及动态变步长扩展策略;最后,针对路径上冗余点多以及曲率不连续的问题,提出考虑安全距离的剪枝优化和三次B样条曲线对初始路径进行拟合优化。仿真结果表明,在不同地图的路径规划中,相比于传统RRT算法,增强了通过狭窄通道能力,优化了路径的平滑性,搜索时间、迭代次数、路径长度分别减少约70%、40%、15%;相比于RRT衍生算法RRT-Connect,搜索时间、路径长度分别减少约25%、10%。展开更多
We present an integrated mathematical model of vehicle-following control for the establishment, maintenance, and re-establishment of the previous or new safe and efficient steady-following state. The hyperbolic functi...We present an integrated mathematical model of vehicle-following control for the establishment, maintenance, and re-establishment of the previous or new safe and efficient steady-following state. The hyperbolic functions are introduced to establish the corresponding mathematical models, which can describe the behavioral adjustment of the following vehicle steered by a well-experienced driver under complex vehicle following situations. According to the proposed mathematical models, the control laws of the following vehicle adjusting its own behavior can be calculated for its moving in safety,efficiency, and smoothness(comfort). Simulation results show that the safe and efficient steady-following state can be well established, maintained, and re-established by its own smooth(comfortable) behavioral adjustment with the synchronous control of the following vehicle’s velocity, acceleration, and the actual following distance.展开更多
文摘快速扩展随机树算法(rapidly-exploring random trees,RRT)规划移动机器人路径时,存在搜索盲目性强、搜索时间长、收敛速度慢、路径冗余点多且不平滑等问题。鉴于此,提出一种改进的RRT路径规划算法。首先,针对传统RRT算法盲目搜索以及局部极值的问题,提出概率目标偏置与人工势场结合的采样策略,引导随机树的扩展;其次,针对随机树扩展的避障能力差的问题,提出基于安全距离的碰撞检测以及动态变步长扩展策略;最后,针对路径上冗余点多以及曲率不连续的问题,提出考虑安全距离的剪枝优化和三次B样条曲线对初始路径进行拟合优化。仿真结果表明,在不同地图的路径规划中,相比于传统RRT算法,增强了通过狭窄通道能力,优化了路径的平滑性,搜索时间、迭代次数、路径长度分别减少约70%、40%、15%;相比于RRT衍生算法RRT-Connect,搜索时间、路径长度分别减少约25%、10%。
基金supported by the National Natural Science Foundation of China(Grant No.61174183)
文摘We present an integrated mathematical model of vehicle-following control for the establishment, maintenance, and re-establishment of the previous or new safe and efficient steady-following state. The hyperbolic functions are introduced to establish the corresponding mathematical models, which can describe the behavioral adjustment of the following vehicle steered by a well-experienced driver under complex vehicle following situations. According to the proposed mathematical models, the control laws of the following vehicle adjusting its own behavior can be calculated for its moving in safety,efficiency, and smoothness(comfort). Simulation results show that the safe and efficient steady-following state can be well established, maintained, and re-established by its own smooth(comfortable) behavioral adjustment with the synchronous control of the following vehicle’s velocity, acceleration, and the actual following distance.