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Evolutionary programming-based univector field navigation method for past mobile robots

Yong‐Jae Kim, Jong-Hwan Kim, Dong‐Soo Kwon

发表年份
2001
引用次数
44

摘要

Most of navigation techniques with obstacle avoidance do not consider the robot orientation at the target position. These techniques deal with the robot position only and are independent of its orientation and velocity. To solve these problems this paper proposes a novel univector field method for fast mobile robot navigation which introduces a normalized two dimensional vector field. The method provides fast moving robots with the desired posture at the target position and obstacle avoidance. To obtain the sub-optimal vector field, a function approximator is used and trained by evolutionary programming. Two kinds of vector fields are trained, one for the final posture acquisition and the other for obstacle avoidance. Computer simulations and real experiments are carried out for a fast moving mobile robot to demonstrate the effectiveness of the proposed scheme.

关键词

Obstacle avoidanceMobile robotObstaclePosition (finance)Computer scienceArtificial intelligenceComputer visionRobotOrientation (vector space)Field (mathematics)

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