RoboCup小型组足球机器人路径规划关键技术研究
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摘要
路径规划是所有移动机器人必须解决的核心问题,包括解决沿着什么路径到达目的地,采用什么速度、如何在指定时间内完成实时规划、如何保证机器人在不违反自身运动学规律情况下跟随规划、如何检测碰撞并避免碰撞、以及如何整定系统参数等诸多子问题。经过几十年的研究与实践,人们在移动机器人路径规划方面积累了大量的研究成果,但仍存在许多问题有待深入研究。
RoboCup即机器人世界杯足球锦标赛,是一项国际比赛盛事。RoboCup小型组足球机器人是RoboCup的主要项目之一,该项目对实时性要求比较高,是进行路径实时规划研究的理想平台。本文针对该项目技术要求进行了路径规划关键问题的研究和实验。取得的结果不仅可直接应用于RoboCup各类比赛,而且还可应用到机器人学等众多领域相关问题的求解。因此,研究工作具有重要理论意义和实际应用价值。
本文在以下几个方面进行了创新性研究：
1)改进了RoboCup小型组机器人碰撞检测算法。碰撞检测前,对障碍数据进行预处理：机器人障碍使用圆形包围盒,障碍物采用KD树结构存储。将包围盒法和空间分割法组合起来,提出了基于KD树和圆形包围盒的碰撞检测方法,该方法减少了系统进行圆形包围盒碰撞检测的次数,降低了算法复杂度,加快了障碍检测速度。
2)改进了随机路径规划算法,提出基于边界的随机路径规划新算法BRRT,研究了障碍边界表示、边界点裁剪方法、以及算法工作流程和相关路径平滑算法。对比了随机路径规划算法改进前后的时间消耗、规划成功率、以及规划路径长度。实验表明改进算法相比原算法时间消耗均匀,规划成功率有所提高,规划路径长度更短,一定程度提高了搜索效率,能有效提高机器人运行平稳性。
3)为了保证机器人的良好运动性能、研究了RoboCup小型组足球机器人四轮协调运动的PI参数整定工作,基于遗传算法提出了四轮协调运动的PI参数自动智能整定新算法,设计了算法中的染色体编码解码方法、适应度函数、遗传算子。实验表明,该算法相比传统的机器人整定方法能提高系统运行稳定性和参数整定效率。
4)针对机器人在运行中可能与障碍碰撞而产生的安全问题,分析了RoboCup小型组项目的障碍类型,以及与碰撞相关的机器人运动学规律,设计了一种动态运动规划算法,基于该算法实时检测机器人在运动中是否会产生碰撞,如果有碰撞危险,通过修正可能发生碰撞的机器人在当前控制周期的加速度达到避免实时碰撞的目的。
Path planning is the core problem facing all mobile robots. This involves a number of problems like along which path and at what speed to come to the destination, how to perform the real-time planning within a designated time frame, how to ensure that the robots will follow these plans without going against their own kinetics, how to detect and avoid collisions, and how to set the system parameters. After decades of research and practice, a large amount of research has been accumulated in path planning of mobile robot, but there are still plenty of problems to intensive study. After decades of research and practice, a large amount of research has been accumulated in path planning of mobile robot, but there are still plenty of problems to intensive study.
RoboCup, i.e., robot world cup soccer games. Small size league soccer league is one of the principal games of RoboCup that requires high real-time level and therefore offers an ideal platform for researches on real-time path planning. In this paper, some key issues relating to path planning are investigated and experimented. The obtained results can not only be applied to various competitions of RoboCup, but also be used to solve the problems of robotics. Consequently, the study will provide both significant theoretical and practical value. The obtained results can not only be applied to various competitions of RoboCup, but also be used to solve the problems of robotics. Consequently, the study will provide both significant theoretical and practical value.
The innovative research has been performed to the following aspects:
1) In practice, a linear chain list is often used by competition teams to store obstacles. Before collision test, the obstacle data are pretreated with a round bounding box for the robots and KD tree structural storage for the obstacles. By combining bounding box method with space-based segmentation algorithm, a collision test method based on KD tree and round bounding box is proposed, which reduces the number of bounding box collision tests, relieves the complexity of the algorithm and accelerates the obstacle test rate.
2)Modified algorithms based on stochastic path planning like ERRT, CRRT, DRRT and MP-RRT are used by leading small size RoboCup league teams and all involve replanning of the path by RRT when there is a material change in the target point. However, as RRT planning has a high randomicity level, there have been cases when the planning was materially overtime and could not meet the real timeliness of small size RoboCup league. This shows certain probability of inability to meet the real timeliness of the system.
3) To ensure sound kinetic property of the robots, the PI parameter setting of the four-wheel synergic movement of small-size RoboCup soccer teams is studied, a new automatic Intelligent PI parameter setting algorithm of the four-wheel synergic movement is proposed based on genetic algorithm, and the chromosome coding and decoding method, fitness function and genetic operator involved in the algorithm. Experiments show that this algorithm achieves higher system operation stability and parameter setting efficiency than conventional robot setting algorithms.
4) To solve the safety of robots against potential collision with obstacles during operation, the type of obstacles in small-size RoboCup games as well as collision-related kinematics of robots is investigated, and a dynamic kinetics planning algorithm is designed, based on which the collision potential for robots during their movement is tested on real-time basis, and where there is a risk to collision, the acceleration of the robot exposed to collision in the present controlled period is corrected to avoid real-time collision.
RoboCup即机器人世界杯足球锦标赛,是一项国际比赛盛事。RoboCup小型组足球机器人是RoboCup的主要项目之一,该项目对实时性要求比较高,是进行路径实时规划研究的理想平台。本文针对该项目技术要求进行了路径规划关键问题的研究和实验。取得的结果不仅可直接应用于RoboCup各类比赛,而且还可应用到机器人学等众多领域相关问题的求解。因此,研究工作具有重要理论意义和实际应用价值。
本文在以下几个方面进行了创新性研究：
1)改进了RoboCup小型组机器人碰撞检测算法。碰撞检测前,对障碍数据进行预处理：机器人障碍使用圆形包围盒,障碍物采用KD树结构存储。将包围盒法和空间分割法组合起来,提出了基于KD树和圆形包围盒的碰撞检测方法,该方法减少了系统进行圆形包围盒碰撞检测的次数,降低了算法复杂度,加快了障碍检测速度。
2)改进了随机路径规划算法,提出基于边界的随机路径规划新算法BRRT,研究了障碍边界表示、边界点裁剪方法、以及算法工作流程和相关路径平滑算法。对比了随机路径规划算法改进前后的时间消耗、规划成功率、以及规划路径长度。实验表明改进算法相比原算法时间消耗均匀,规划成功率有所提高,规划路径长度更短,一定程度提高了搜索效率,能有效提高机器人运行平稳性。
3)为了保证机器人的良好运动性能、研究了RoboCup小型组足球机器人四轮协调运动的PI参数整定工作,基于遗传算法提出了四轮协调运动的PI参数自动智能整定新算法,设计了算法中的染色体编码解码方法、适应度函数、遗传算子。实验表明,该算法相比传统的机器人整定方法能提高系统运行稳定性和参数整定效率。
4)针对机器人在运行中可能与障碍碰撞而产生的安全问题,分析了RoboCup小型组项目的障碍类型,以及与碰撞相关的机器人运动学规律,设计了一种动态运动规划算法,基于该算法实时检测机器人在运动中是否会产生碰撞,如果有碰撞危险,通过修正可能发生碰撞的机器人在当前控制周期的加速度达到避免实时碰撞的目的。
Path planning is the core problem facing all mobile robots. This involves a number of problems like along which path and at what speed to come to the destination, how to perform the real-time planning within a designated time frame, how to ensure that the robots will follow these plans without going against their own kinetics, how to detect and avoid collisions, and how to set the system parameters. After decades of research and practice, a large amount of research has been accumulated in path planning of mobile robot, but there are still plenty of problems to intensive study. After decades of research and practice, a large amount of research has been accumulated in path planning of mobile robot, but there are still plenty of problems to intensive study.
RoboCup, i.e., robot world cup soccer games. Small size league soccer league is one of the principal games of RoboCup that requires high real-time level and therefore offers an ideal platform for researches on real-time path planning. In this paper, some key issues relating to path planning are investigated and experimented. The obtained results can not only be applied to various competitions of RoboCup, but also be used to solve the problems of robotics. Consequently, the study will provide both significant theoretical and practical value. The obtained results can not only be applied to various competitions of RoboCup, but also be used to solve the problems of robotics. Consequently, the study will provide both significant theoretical and practical value.
The innovative research has been performed to the following aspects:
1) In practice, a linear chain list is often used by competition teams to store obstacles. Before collision test, the obstacle data are pretreated with a round bounding box for the robots and KD tree structural storage for the obstacles. By combining bounding box method with space-based segmentation algorithm, a collision test method based on KD tree and round bounding box is proposed, which reduces the number of bounding box collision tests, relieves the complexity of the algorithm and accelerates the obstacle test rate.
2)Modified algorithms based on stochastic path planning like ERRT, CRRT, DRRT and MP-RRT are used by leading small size RoboCup league teams and all involve replanning of the path by RRT when there is a material change in the target point. However, as RRT planning has a high randomicity level, there have been cases when the planning was materially overtime and could not meet the real timeliness of small size RoboCup league. This shows certain probability of inability to meet the real timeliness of the system.
3) To ensure sound kinetic property of the robots, the PI parameter setting of the four-wheel synergic movement of small-size RoboCup soccer teams is studied, a new automatic Intelligent PI parameter setting algorithm of the four-wheel synergic movement is proposed based on genetic algorithm, and the chromosome coding and decoding method, fitness function and genetic operator involved in the algorithm. Experiments show that this algorithm achieves higher system operation stability and parameter setting efficiency than conventional robot setting algorithms.
4) To solve the safety of robots against potential collision with obstacles during operation, the type of obstacles in small-size RoboCup games as well as collision-related kinematics of robots is investigated, and a dynamic kinetics planning algorithm is designed, based on which the collision potential for robots during their movement is tested on real-time basis, and where there is a risk to collision, the acceleration of the robot exposed to collision in the present controlled period is corrected to avoid real-time collision.
引文
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