基于RoboCup3D仿真平台的双足机器人大脚球进攻策略设计

RoboCup3D仿真系统融合了人工智能、传感器、通信、智能控制等多门学科的相关技术.针对RoboCup3D仿真中双足机器人的踢球动作设计问题(如:踢球力度弱、摔倒等)提出了一种基于大脚球的进攻策略.采用大脚球的进攻策略可以有效的促使足球快速的踢进对方半场后方,在仿真比赛中极具攻击性.仿真结果验证了它的有效性和实用性.     

一种基于统计的多智能体Q学习算法

针对非确定马尔可夫环境下的多智能体系统,提出了一种新的基于统计的多智能体Q学习算法,该算法将统计学习与增强学习有机结合,有效地解决了智能体环境部分感知、信息不确定以及其他智能体行为策略学习的问题,经RoboCup仿真实验证明该算法具有较强的自适应能力和学习效率。     

Dynamic control of steerable wheeled mobile platforms applied to an eight-wheeled RoboCup Middle Size League soccer robot

In the RoboCup Middle Size League two teams of mobile robots play soccer against each other. During the game, agility, i.e. the ability to quickly change the direction of platform movements, is important to react or anticipate fast on the intention of opponents to efficiently perform maneuvers like ball shielding and interception. Therefore, high accelerations are desired which ideally would ask all wheels to contribute to traction in the target direction. However none of the current omnidirectional wheel-based robots in the league offers such a feature. Each pair of wheels can rotate independently about its suspension axis . The new configuration brings new challenges in control: the platform becomes kinematically nonholonomic due to the kinematic constraints around the pivot axes, but it is shown that in the context of the driving task the controller can keep the wheel configurations such that they can generate a force and torque in the directions needed by the task. Hereby, the restriction to minimize the position-error in its three degrees of freedom with respect to a predefined trajectory is relaxed by taking only the degrees of freedom relevant for the task into consideration. A cascaded control strategy is proposed that combines kinematic and dynamic control and also addresses the control-allocation problem. Compared to a full kinematic approach as typically applied on steerable wheeled systems, 2.3 times higher translational and 1.8 times higher angular velocity are demonstrated. For the translational acceleration and angular acceleration, improvement factors of 2.7 and 3.2 are achieved, respectively. The platform made a successful debut during the RoboCup Portuguese Open 2019, showing the robustness of the proposed approach.     

A robust omnidirectional vision sensor for soccer robots

How to make robot vision work robustly under varying lighting conditions and without the constraint of the current color-coded environment are two of the most challenging issues in the RoboCup community. In this paper, we present a robust omnidirectional vision sensor to deal with these issues for the RoboCup Middle Size League soccer robots, in which two novel algorithms are applied. The first one is a camera parameters auto-adjusting algorithm based on image entropy. The relationship between image entropy and camera parameters is verified by experiments, and camera parameters are optimized by maximizing image entropy to adapt the output of the omnidirectional vision to the varying illumination. The second one is a ball recognition method based on the omnidirectional vision without color classification. The conclusion is derived that the ball on the field can be imaged to be an ellipse approximately in our omnidirectional vision, and the arbitrary FIFA ball can be recognized by detecting the ellipse imaged by the ball. The experimental results show that a robust omnidirectional vision sensor can be realized by using the two algorithms mentioned above.     

A novel ball handling mechanism for the RoboCup middle size league

This paper presents the hardware design and control design of a novel ball handling mechanism in the RoboCup Middle Size League used by team Tech United Eindhoven. The ball handling mechanism consist of two levers with two actively driven wheels attached to it, to exert forces on the ball in order to control its position relative to the robot. The proposed design is fully compliant to the rules and regulations imposed by the RoboCup Middle Size League community. The control design consists of a cascaded velocity and position feedback loop in combination with a feedforward controller which compensates for the robots ego motion. The proposed design is validated on a robot used by the Tech United Eindhoven team.     

基于CMAC的Q算法在机器人足球中的应用

RoboCup是全球影响力最大的机器人足球比赛，是机器人学和人工智能及其应用的标准研究问题之一。仿真组在RoboCup中是重要的一部分。由于仿真组的比赛环境非常复杂，采用手工编码实现的Agent的高层决策无法考虑到比赛的所有情况，缺乏灵活性，并且需要花大量的时间对手工编码中的参数进行调整，结果也不是很理想。所以本文采用机器学习来实现Agent的决策。本文运用了一种基于CMAC的Q学习方法，把该方法应用在禁区内进行2VSl进攻的策略学习训练实例中，实验结果表明了本方法的可行性和有效性。     

一种F180型足球机器人控制系统的研制

介绍了一种RoboCup小型组机器人(F180)的控制系统,该系统以通用性和功能完备为目标,包括主控电路、无线通讯、执行机构(踢球和带球机构等)以及传感器电路等子系统。系统以PIC16F877A单片机为核心,用PWM输出控制直流电机,用计数器检测轮速形成闭环控制,用I/O口控制继电器驱动踢球带球机构,用通用同步/异步收发器(USART)扩展进行无线通讯。实验证明,该控制系统运行效果良好,机器人具备了进行比赛的能力。     

基于动态阈值的寻迹车控制算法的研究

在参加RoboCup中国机器人大赛＂机器人游中国＂的项目过程中,研究并设计了多种方案,根据现场测试结果,对智能车的巡线识别、运动控制及智能判断算法做了进一步的研究,提出并实现了动态阈值算法、快速稳定的转弯与停车控制、出线自动找回技术等3种新颖、实用的智能车控制算法。     

中型组机器人运动控制系统的FPGA设计

以RoboCup中型组足球机器人为实验平台,提出一种基于FPGA的全方位移动足球机器人运动控制系统的实现方法。首先分析和研究三轮全方位移动机器人的运动学特性,建立其运动控制模型,然后以FPGA为主要处理器,设计了PID速度闭环控制算法,实现了对机器人的精确控制。实验发现,该设计方法具有很好的实时性,能够对全方位移动机器人进行快速、准确的控制。     

RoboCup机器人足球仿真比赛开发设计流程

机器人世界杯足球锦标赛(The Robot World Cup)，简称RoboCup，通过提供一个标准任务来促进分布式人工智能、智能机器人技术及其相关领域的研究与发展。在介绍RoboCup仿真环境的基础上，系统完整地介绍了客户端程序的开发设计流程，阐述了其中涉及到的一些主要问题和算法，最后简要综述目前国际上的典型高层算法结构。希望能够对开展机器人足球比赛及相关领域的研究有启发意义。