AN ACTION GENERATION MODEL BY USING TIME SERIES PREDICTION AND ITS APPLICATION TO ROBOT NAVIGATION-Reference-Cited by-同舟云学术

AN ACTION GENERATION MODEL BY USING TIME SERIES PREDICTION AND ITS APPLICATION TO ROBOT NAVIGATION

Published:2009-04 Issue:02 Volume:19 Page:105-113
ISSN:0129-0657
Container-title:International Journal of Neural Systems
language:en
Short-container-title:Int. J. Neur. Syst.

Author:

GOUKO MANABU¹,ITO KOJI¹

Affiliation:

1. Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama, 226-8502, Japan

Abstract

This paper proposes an action generation model which consists of many motor primitive modules. The motor primitive modules output motor commands based on sensory information. Complicated behavior is generated by sequentially switching the modules. The model also has a prediction unit. This unit predicts which module will be used for current action generation. We have confirmed the effectiveness of the model by applying it to a robot navigation task simulation, and have investigated the influence of the prediction on the action generation.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Networks and Communications,General Medicine

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0129065709001872

Reference5 articles.

1. Finding Structure in Time

2. How Hierarchical Control Self-organizes in Artificial Adaptive Systems

3. Learning to perceive the world as articulated: an approach for hierarchical learning in sensory-motor systems

4. Multiple paired forward and inverse models for motor control

5. An associative memory system for sequential learning using reliability of memorized patterns

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning of the Exploratory Behavior of Mobile Robots for Environmental Segmentation;2024 10th International Conference on Automation, Robotics and Applications (ICARA);2024-02-22

2. Reduction of Delay in Detecting Initial Dips from Functional Near-Infrared Spectroscopy Signals Using Vector-Based Phase Analysis;International Journal of Neural Systems;2016-04-07

3. Removal of dynamic weather conditions based on variable time window;IET Computer Vision;2013-08

4. DISCOVERING SIGNIFICANT EVOLUTION PATTERNS FROM SATELLITE IMAGE TIME SERIES;International Journal of Neural Systems;2011-12

5. Feature extraction for classification of different weather conditions;Frontiers of Electrical and Electronic Engineering in China;2011-06