Cooperative 3-Robot Passing and Shooting in the RoboCup Small Size League

Nakanishi, Ryota; Bruce, James; Murakami, Kazuhito; Naruse, Tadashi; Veloso, Manuela

doi:10.1007/978-3-540-74024-7_41

Cited by 16 publications

(6 citation statements)

References 2 publications

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“…Schwab et al [14] used DDPG algorithm to realize skills learning such as ball finding and shooting, and transferred from simulation to actual robots. In the aspect of cooperation and confrontation between multiple agents, Nakanishi et al [15] studied and analyzed the cooperative passing and shooting task of three robots, and achieved a high success rate in the test of actual robots. Trevizan et al [16] used the method of machine learning to propose a similarity function, which compares two teams by imitating the behavior of another team, so as to formulate their strategies.…”

Section: Related Workmentioning

confidence: 99%

Multi-agent Collaboration for Feasible Collaborative Behavior Construction and Evaluation

An-Lan

Jia

Chen

et al. 2019

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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In the case of the two-person zero-sum stochastic game with a central controller, this paper proposes a best collaborative behavior search and selection algorithm based on reinforcement learning, in response to how to choose the best collaborative object and action for the central controller. In view of the existing multi-agent collaboration and confrontation reinforcement learning methods, the methods of traversing all actions in a certain state leads to the problem of long calculation time and unsafe policy exploration. This paper proposes to construct a feasible collaborative behavior set by using action space discretization, establishing models of both sides, modelbased prediction and parallel search. Then, we use the deep qlearning method in reinforcement learning to train the scoring function to select the optimal collaboration behavior from the feasible collaborative behavior set. This method enables efficient and accurate calculation in an environment with strong confrontation, high dynamics and a large number of agents, which is verified by the RoboCup Small Size League robots passing collaboration.

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Section: Related Workmentioning

confidence: 99%

Multi-agent Collaboration for Feasible Collaborative Behavior Construction and Evaluation

An-Lan

Jia

Chen

et al. 2019

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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“…The Skills-Tactics-Plays (STP) architecture [11] was among the first formal approaches to plan for coordination among teammates, and is still used by most of the teams in the SSL. More recently, there has been an increasing interest in modeling opponents in order to learn their plays [12], robot ball passing and shooting [13], and dynamic selection, planning and learning of behaviors and strategies [14,15]. Robot deception, in the form of the "Coerce And Attack Planner" [16], was introduced in the SSL in RoboCup 2013 to coerce opponents away from strategic locations, allowing goals to be scored by exploiting the strategic openings.…”

Section: Artificial Intelligence and Team Coordinationmentioning

confidence: 99%

RoboCup Small-Size League: Past, Present and Future

Weitzenfeld

Biswas

Akar

et al. 2015

RoboCup 2014: Robot World Cup XVIII

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The Small Size Robot League (SSL) was among the founding RoboCup leagues in the 1997 competition held during IJCAI'97 in Nagoya, Japan. Since then, the league has experienced various advances in terms of robot design, number of robots, field size, software algorithms and other infrastructure used during the games, among these the recent standardization of the vision system shared by all teams. The SSL league has been one of the fastest paced leagues in RoboCup where teamwork, coordination, high-level strategies and artificial intelligence have played a critical role in the league development. As robots speeds have greatly increased in the past years, the league has witnessed the development of advanced control and cooperative algorithms. In parallel, shared open software, in particular the shared vision system has made it easier for new teams to join the league. In this paper we discuss the past, present and future of the Small Size League in its path towards the goal of achieving robot vs. human soccer in 2050.

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“…Meanwhile, the bottom hardware control system was also addressed, like the structure design of the control system and the choice of the hardware unit [8,9] . Some of them might be focused on the realization of certain behavior, for example obstacle avoidance [10,11] and shooting [12] . These studies prompted the development of robots.…”

Section: Introductionmentioning

confidence: 99%

Action control of soccer robots based on simulated human intelligence

Shao

2010

Int. J. Autom. Comput.

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A multi-modal action control approach is proposed for an autonomous soccer robot when the bottom hardware is unchangeable. Different from existing methods, the proposed control approach defines actions with the principle of "perception-planning-action" inspired by human intelligence. Character extraction is used to divide the perception input into different modes. Different control modes are built by combining different control methods for the linear velocity and angular velocity. Based on production rules, the motion control is realized by connecting different perceptions to the corresponding control mode. Simulation and real experiments are conducted with the middle-sized robot Frontier-I, and the proposed method is compared with a proportional-integral-derivative (PID) control method to display its feasibility and performance. The results show that the multi-modal action control method can make robots react rapidly in a dynamic environment.

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Cooperative 3-Robot Passing and Shooting in the RoboCup Small Size League

Cited by 16 publications

References 2 publications

Multi-agent Collaboration for Feasible Collaborative Behavior Construction and Evaluation

Multi-agent Collaboration for Feasible Collaborative Behavior Construction and Evaluation

RoboCup Small-Size League: Past, Present and Future

Action control of soccer robots based on simulated human intelligence

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