Potential Field Approach to Short Term Action Planning in RoboCup F180 League

Nagasaka, Yasunori; Murakami, Kazuhito; Naruse, Tadashi; Takahashi, Tomoichi; Mori, Yasuo

doi:10.1007/3-540-45324-5_37

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…We used the potential-fields to represent all game situations. But in addition to [Nagasaka et al, 2000] we use it for all possible actions, not only for a kick. We used it to decide which action we make and what the situation is.…”

Section: Resultsmentioning

confidence: 99%

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Decision-Making and Tactical Behavior with Potential Fields

Meyer

Adolph

Stephan

et al. 2003

Lecture Notes in Computer Science

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Using potential-fields is a seldomly used technique in RoboCup scenarios. The existing approaches mainly concentrate on world state representation on single actions such as a kick. In this paper we will show how to apply potential fields to assist fast and precise decisions in an easy and intuitive way. We go beyond the existing approaches in using potential fields to determine all possible player actions, basic and advanced tactics an also general player behaviors. To ensure fast computing we mainly use basic mathematical computation for potential field related calculations. This gives us the advantage of both determining and understanding player actions. Therefore, integrating future features such as a complex online coach and progressive localization methods will be easier. We implemented the approach in our team Bremen University Goal Seekers (BUGS) and tested it in numerous games against other simulation league teams. The results show that CPU-time of making a decision per team has been decreased significantly. This is a crucial improvement for calculations in time-critical environments.

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Section: Resultsmentioning

confidence: 99%

“…This means that we use potential fields to derive any decision that has to be made by an agent. [Nagasaka et al, 2000] use potential fields for actions like a single kick. Our general usability approach goes further.…”

Section: Introductionmentioning

confidence: 99%

Decision-Making and Tactical Behavior with Potential Fields

Meyer

Adolph

Stephan

et al. 2003

Lecture Notes in Computer Science

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“…At the team level, a number of teams use potential field based techniques for team control in the SSL (e.g., [22,39,28]). Potential field based team control is also popular outside of the SSL, in the mid-size [34], simulation [27] and Sony AIBO legged leagues [20].…”

Section: Related Workmentioning

confidence: 99%

STP: Skills, tactics, and plays for multi-robot control in adversarial environments

Browning

Bruce

Bowling

et al. 2005

Proceedings of the Institution of Mechanical Engineers, Part I:

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In an adversarial multi-robot task, such as playing robot soccer, decisions for team and single robot behavior must be made quickly to take advantage of short-term fortuitous events when they occur. When no such opportunities exist, the team must execute sequences of coordinated action across team members that increases the likelihood of future opportunities. We have developed a hierarchical architecture, called STP, to control an autonomous team of robots operating in an adversarial environment. STP consists of Skills for executing the low-level actions that make up robot behavior, Tactics for determining what skills to execute, and Plays for coordinating synchronized activity amongst team members. Our STP architecture combines each of these components to achieve autonomous team control. Moreover, the STP hierarchy allows for fast team response in adversarial environments while carrying out actions with longer goals. In this article, we present our STP architecture for controlling an autonomous robot team in a dynamic adversarial task that allows for coordinated team activity towards long-term goals, with the ability to respond rapidly to dynamic events. Secondly, we present the sub-component of skills and tactics as a generalized, single-robot control hierarchy for hierarchical problem decomposition with flexible control policy implementation and reuse. Thirdly, we contribute our play techniques as a generalized method for encoding and synchronizing team behavior, providing multiple competing team responses, and for supporting effective strategy adaptation against opponent teams. STP has been fully implemented on a robot platform and thoroughly tested against a variety of unknown opponent teams under in a number of RoboCup robot soccer competitions. We present these competition results as a mechanism to analyze the performance of STP in a real setting.

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“…Inaccuracy of the direction should be compensated in the path generation system. The path generation system generates and evaluates a path from a current position to a target position, where the target position is given by the strategy system [4]. Moreover, there is a constraint to control the direction, since our robot has only 2 wheels.…”

Section: Path Generationmentioning

confidence: 99%

Fast Image Processing and Flexible Path Generation System for RoboCup Small Size League

Hibino

Kodama

Nagasaka

et al. 2003

RoboCup 2002: Robot Soccer World Cup VI

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Two key features of successful multi-robot systems in RoboCup are robustness of a vision system and optimization of feedback control in order to reach the goal point and generate the action under the team strategy. This paper proposes two new methods. One is a fast image processing method, which is coped with the spatial variance of color parameters in the field, to extract the positions of robots and ball in 1/30 sec. The separation problem in the interlaced format image is solved. Another one is a path generation method in which the robot approaches the goal by changing its direction convergently. With these two algorithms, the real time processing system is realized by generating a stable path under a low quality input image.

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Potential Field Approach to Short Term Action Planning in RoboCup F180 League

Cited by 6 publications

References 3 publications

Decision-Making and Tactical Behavior with Potential Fields

Decision-Making and Tactical Behavior with Potential Fields

STP: Skills, tactics, and plays for multi-robot control in adversarial environments

Fast Image Processing and Flexible Path Generation System for RoboCup Small Size League

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