Path planning and obstacle avoidance are two challenging problems in the study of intelligent robots. In this paper, we develop a new method to alleviate these problems based on deep Q-learning with experience replay ...Path planning and obstacle avoidance are two challenging problems in the study of intelligent robots. In this paper, we develop a new method to alleviate these problems based on deep Q-learning with experience replay and heuristic knowledge. In this method, a neural network has been used to resolve the "curse of dimensionality" issue of the Q-table in reinforcement learning. When a robot is walking in an unknown environment, it collects experience data which is used for training a neural network;such a process is called experience replay.Heuristic knowledge helps the robot avoid blind exploration and provides more effective data for training the neural network. The simulation results show that in comparison with the existing methods, our method can converge to an optimal action strategy with less time and can explore a path in an unknown environment with fewer steps and larger average reward.展开更多
本研究采用CiteSpace对知网及Web of Science 2016—2020年老年人用户体验研究文献记录进行知识图谱分析。结果显示:(1)国际研究里西方发达国家影响较大;(2)国内研究尚未形成聚焦的应用领域,国际研究聚焦于医疗健康领域;(3)生活质量成...本研究采用CiteSpace对知网及Web of Science 2016—2020年老年人用户体验研究文献记录进行知识图谱分析。结果显示:(1)国际研究里西方发达国家影响较大;(2)国内研究尚未形成聚焦的应用领域,国际研究聚焦于医疗健康领域;(3)生活质量成为近几年国际研究热点;(4)国际研究的知识基础可分为设计理念与评价、医疗健康和新兴技术三类。我国研究者未来可关注老年人具体产品或服务的设计理念、医疗健康、交互设计以及效果评价的适老化等领域。展开更多
基金supported by the National Natural Science Foundation of China(61751210,61572441)。
文摘Path planning and obstacle avoidance are two challenging problems in the study of intelligent robots. In this paper, we develop a new method to alleviate these problems based on deep Q-learning with experience replay and heuristic knowledge. In this method, a neural network has been used to resolve the "curse of dimensionality" issue of the Q-table in reinforcement learning. When a robot is walking in an unknown environment, it collects experience data which is used for training a neural network;such a process is called experience replay.Heuristic knowledge helps the robot avoid blind exploration and provides more effective data for training the neural network. The simulation results show that in comparison with the existing methods, our method can converge to an optimal action strategy with less time and can explore a path in an unknown environment with fewer steps and larger average reward.
文摘本研究采用CiteSpace对知网及Web of Science 2016—2020年老年人用户体验研究文献记录进行知识图谱分析。结果显示:(1)国际研究里西方发达国家影响较大;(2)国内研究尚未形成聚焦的应用领域,国际研究聚焦于医疗健康领域;(3)生活质量成为近几年国际研究热点;(4)国际研究的知识基础可分为设计理念与评价、医疗健康和新兴技术三类。我国研究者未来可关注老年人具体产品或服务的设计理念、医疗健康、交互设计以及效果评价的适老化等领域。
