Patrick Bonnin

Vision, Strategy, and Localization Using the Sony Robots at RoboCup-98

Sony has provided a robot platform for research and development in physical agents, namely, fully autonomous legged robots. In this article, we describe our work using Sonys legged robots to participate at the RoboCup-98 legged robot demonstration and competition. Robotic soccer represents a challenging environment for research in systems with multiple robots that need to achieve concrete objectives, particularly in the presence of an adversary. Furthermore, RoboCup offers an excellent opportunity for robot entertainment. We introduce the RoboCup context and briefly present Sonys legged robot. We developed a vision-based navigation and a Bayesian localization algorithm. Team strategy is achieved through predefined behaviors and learning by instruction.

A new video rate region color segmentation and classification for sony legged robocup application

Whereas numerous methods are used for vision systems embedded on robots, only a few use colored region segmentation mainly because of the processing time. In this paper, we propose a real-time (i.e. video rate) color region segmentation followed by a robust color classification and region merging dedicated to various applications such as RoboCup four-legged league or an industrial conveyor wheeled robot. Performances of this algorithm and confrontation with other existing methods are provided.

Reactive and adaptive control architecture designed for the Sony legged robots league in RoboCup 1999

This paper deals with the description of the strategy adopted by the French team in the Sony legged league to play soccer. Not only the behaviors designed for RoboCup are presented, but also the arrangement of the three different modules inside the robot, namely the vision, locomotion and strategy modules. The vision module runs at lower priority and provides others with relevant information captured from the environment. The locomotion module is responsible for the walking gaits generation. It manages transitions between forward, turning and rotation modes. It incorporates changes in speed, and recovery procedures in case the robot falls down. The paper focuses on how the decision or other behaviors are being taken. The overall architecture and the communications between the three modules are also described.

Trot Gait Design Details for Quadrupeds

This paper presents a full description of the design of a trot locomotion that has been implemented on AIBO quadrupeds in the Sony legged league. This work is inspired by the UNSW achievements in RoboCup 2000 and 2001 in Melbourne and Seattle. The French team rebuilt a complete trot locomotion from scratch, and introduced special features that differ from the Australian original design. Many papers have already been dedicated to the work on quadruped locomotion [2-4]. However they do not detail all the parts of the design.

How to introduce a priori visual and behavioral knowledge for autonomous and mobile robots to operate in known environments

To operate in a known and dynamic environment, a robot needs two different kinds of a priori knowledge : behavioral and visual. In this paper we propose a general methodology to introduce this a priori knowledge, and we illustrate it by an application : the software developments for the AIBO robots to play soccer. The more difficult task is to extract reliable visual information. It is the reason why a priori knowledge is already introduced at the level of vision processing. Without reliable vision information it is impossible for the robot to switch to the tight behavior, and consequently to play.

Speed control for quadruped using duty factor

This work deals with the design of a locomotion algorithm that changes the speed of a crawling quadruped by varying the duty factor /spl beta/. The walking pattern used is the well-known wave gait. This kind of gait should be maintained as much as possible since it is the most efficient locomotion pattern on flat ground. However, the transition between initial and final gaits cannot be based on a wave gait any more because support legs have to be resynchronized according to a new duty factor. This paper proposes an algorithm that deals with the gait transition between initial and final duty factors.

Quadruped Robot Guided by Enhanced Vision System and Supervision Modules

Legged robots taking part in real multi-agent activities represent a very innovative challenge. This domain of research requires developments in three main areas. First the robot must be able to move efficiently in every direction in its environment. The faster the motion, the better it is. Special care must be taken when designing walking pattern transitions. Then, without any exteroceptive sensor to get information about its surroundings, the robot is blind. Fortunately, the quadruped prototype on which all experiments are carried out is equipped with a enhanced vision system and vision is the best means of getting a representation of the world that can be found in Nature. Finally the machine should be brought a minimum of intelligence since it has to manage vision information and its walking gaits by itself. When involved in cooperation, confrontation or both like in the soccer play, a high level supervision task is welcome. This paper presents detailed developments of these three points and describes how they are implemented on the real robot.

Towards a method to compare and to evaluate fast pixel gathering mechanisms for real time robotic vision systems

Taking into account the constraints of mobile and autonomous robotics, and the tasks devoted to the vision system embedded on different robots for various applications, we propose a research in matter of fast pixel gathering mechanisms for the connected component extraction and the color region segmentation. In this work, we studied three different mechanisms, and proposed a new method to compare and to evaluate the algorithms according to two criteria: the speed of processing and the quality of the results for robotic applications. This method allows to choose the most appropriate algorithm for a given robotic application, and to create new algorithms, by hybridizing older ones while keeping interesting properties.