An Autonomous Mobile Robot with Functions of Action Learning, Memorizing, Recall and Identifying the Environment Using Gaussian Mixture Model
In this paper, behavior scheme of autonomous mobile robots to achieve the objectives of them in environments are proposed, having function of identifying the current environment in which they are placed and making use of learning, memorizing and recalling behaviors of corresponding to each of plural different environments. Specifically, each robot has the function of identifying the environment using some behavioral statistical data for each environment, and if the robot has already experienced the environment, it behaves by making use of own experienced data stored in the database, otherwise it performs a new behavior learning and adds the learning results into the database.
KeywordsIntelligent robot Chaotic neural network Reinforcement learning Identification of the environment Gaussian mixture model
- 1.Obayashi, M., Narita, K., Kuremoto, T., Kobayashi, K.: A reinforcement learning system with chaotic neural networks-based adaptive hierarchical memory structure for autonomous robots. In: Proceedings of International Conference on Control, Automation and Systems 2008 (ICCAS 2008), pp. 69–74 (2008)Google Scholar
- 2.Obayashi, M., Narita, K., Okamoto, Y., Kuremoto, T., Kobayashi, K., Feng, L.: A reinforcement learning system embedded agent with neural network-based adaptive hierarchical memory structure. In: Advances in Reinforcement Learning, chapter 11, pp.189–208, IN-TECH (2011)Google Scholar
- 4.Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT PRESS, Cambridge (1988)Google Scholar