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摘要: 机器人技能学习是人工智能与机器人学的交叉领域，目的是使机器人通过与环境和用户的交互得到经验数据，基于示教学习或强化学习，从经验数据中自主获取和优化技能，并应用于以后的相关任务中.技能学习使机器人的任务部署更加灵活快捷和用户友好，而且可以让机器人具有自我优化的能力.技能模型是技能学习的基础和前提，决定了技能效果的上限.日益复杂和多样的机器人操作任务，对技能操作模型的设计实现带来了很多挑战.本文给出了技能操作模型的概念与性质，阐述了流程、运动、策略和效果预测四种技能表达模式，并对其典型应用和未来趋势做出了概括.Abstract: Robot skill learning is an interdisciplinary field of artificial intelligence and robotics. The aim is to enable that a robot autonomously obtains a certain manipulation skill via imitation learning or reinforcement learning, based on the experience data generated by the robot's interaction with the environment or human users. Skill learning can make the robot task deployments more flexible, efficient and user-friendly, even realize the sustainable self-improvement of robot. Robot skill model is the foundation of skill learning, which determines upper limit of the skill outcome. The complexity and variety of the modern robot manipulation tasks pose many challenges to the robot skill modeling. This paper describes the definition and characteristics of robot manipulation skill model, introduces the four skill representation methods considering procedure, motion, policy and outcome, respectively. Finally, the typical application and future tendency of robot manipulation skill models are presented.
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Key words:
- Robot manipulation /
- intelligent robot /
- robot learning /
- skill learning /
- autonomous system
1) 本文责任编委 贺威 -
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