HIERARCHICAL TRAJECTORY PLANNING OF REDUNDANT MANIPULATORS WITH STRUCTURED INTELLIGENCE

This paper deals with trajectory generation for redundant manipulators with structured intelligence. Recently, behavior engineering for robo tic systems has been discussed as a new technological discipline. The intelligence of a robot depends on the structure of hardware and softw are for processing information, i.e. the structure determines the pote ntiality of intelligence. This paper proposes a robotic system with st ructured intelligent based on subsumption-like architecture. Based on perceptual information, a robot with structured intelligence makes dec isions and takes action from four levels in parallel. In addition, the robot generates its motion through interaction with the environment a nd, at the same time, gradually acquires its skill based on the genera ted motion. To acquire skill and motion, the robot requires internal a nd external evaluations at least. This paper applies a virus-evolution ary genetic algorithm to trajectory planning for redundant manipulator s with structured intelligence. Furthermore, we discuss its effectiven ess through computer simulation results.