Titlebook: Making Robots Smarter; Combining Sensing an Katharina Morik,Michael Kaiser,Volker Klingspor Book 1999 Springer Science+Business Media New Y

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蒙太奇

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Introduction to Skill Learnings that map robot perceptions directly onto robot actions by means of a strategy (a control function or policy, resp.) that is goal-oriented. Examples of such elementary skills are force control, peg-into-hole insertion, navigation through a door,targeted parameterization of an active sensor system, et cetera.

不能約

TIGER

antidote

Learning Sensor-Based Navigation or the effect of its actions, and learns on-line using only raw sensory data collected as it moves. The experimental results show that a few trials suffice for the robot to navigate efficiently in a real environment of moderate complexity.

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謙卑

Learning To Classifyation problem are outlined. Then we will present the methods and tools that were developed in the context of the work that was being done, namely the pattern recognition toolbox . and the supervised learning algorithm Q*. Finally we will apply the results of the previous theories in the context of Machine tool supervision.

committed

Program Optimization for Real-Time Performancehat speed up its evaluation. These are a program transformation method, a compilation method, and an efficient forward inference method. The latter is part of a performance system capable of inferring high-level concepts from the sensory input of a mobile robot on-line and in real time.

Arbitrary

Contact Estimation for Compliant Motion Controlcribes how this sensory information can be used in an assembly fine-motion planner and also during task execution; two approaches, one analytical and the other learning approaches, are presented and compared.