| 引用本文: | 刘中常,王明杰,郭戈.基于预测窗的轮式移动机器人最优避障避碰算法[J].控制理论与应用,2020,37(5):1045~1053.[点击复制] |
| LIU Zhong-chang,WANG Ming-jie,GUO Ge.The optimal obstacle/collision avoidance algorithm for wheeled mobile robots based on prediction window[J].Control Theory and Technology,2020,37(5):1045~1053.[点击复制] |
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| 基于预测窗的轮式移动机器人最优避障避碰算法 |
| The optimal obstacle/collision avoidance algorithm for wheeled mobile robots based on prediction window |
| 摘要点击 1977 全文点击 729 投稿时间：2019-03-21 修订日期：2019-09-23 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2019.90160 |
| 2020,37(5):1045-1053 |
| 中文关键词 轮式移动机器人 预测窗 加速度变化障碍 相互避碰 避障算法 |
| 英文关键词 wheeled mobile robot prediction window acceleration change obstacles reciprocal collision avoidance obstacle avoidance algorithm |
| 基金项目 国家自然科学基金项目(61703445, 61573077, U1808205), 辽宁省自然科学基金项目(20180540064), 广东省自然科学基金项目(2017A030310050), 大连市科技创新基金项目(2019J12GX040), 中央高校基本科研业务费专项资金项目(3132019107)资助. |
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| 中文摘要 |
| 针对非线性轮式移动机器人的避障以及多机器人间的相互避碰问题, 提出了一种基于预测窗的避障避碰
算法. 首先为了便于预测碰撞的发生, 通过反馈线性化将非线性的机器人运动学模型转化成线性模型; 然后根据线
性模型预测会导致机器人发生碰撞的所有相对虚拟加速度变化量集合, 称之为加速度变化障碍. 基于此, 为每个机
器人构造既能躲避障碍物又能相互避碰的可行加速度变化集合. 然后通过优化指标函数求得最优虚拟加速度变化
量, 最后将其转换成机器人的实际控制量. 这种算法与现有的相比, 可使机器人在避障或避碰过程中的行驶方向
角、线速度的变化幅值更小, 角速度和线加速度的变化更为平顺, 而且运行所用的平均时间更短. 仿真结果演示了
所提出算法的有效性和相对于已有方法的优势. |
| 英文摘要 |
| This paper proposed an obstacle and collision avoidance algorithm for nonlinear wheeled mobile robots,
based on prediction window. First, for ease of predicting potential collisions, the nonlinear kinematics model of each robot
is transformed into a linear model by using the feedback linearization technique. Then, based on the linear models, the set
of all relative virtual acceleration changes that will lead to collision is predicted for each robot, which is called acceleration
change obstacle. Accordingly, the feasible acceleration change set which can avoid collisions with obstacles and other
robots is constructed for each robot. Finally, the optimal virtual acceleration change is obtained by minimizing an index
function, and is further converted into the actual control input of each robot. Compared with existing approaches, the
proposed algorithm can result in smaller variations in each robot’s heading angle and linear velocity, and smoother angular
velocity and linear acceleration during the process of obstacle avoidance or reciprocal collision avoidance. Simulation
results illustrate the effectiveness of the proposed algorithm and its advantages over existing methods. |
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