信息与控制2016，Vol.45Issue(5)：521-529,9.DOI:10.13976/j.cnki.xk.2016.0521
基于学习机制的移动机器人动态场景自适应导航方法
Mobile Robot Adaptive Navigation in Dynamic Scenarios Based on Learning Mechanism
摘要
Abstract
Mobile robot navigation based on a simple learning mechanism is generally applied to static scenarios and has poor adaptability.Therefore,we propose a method of adaptive navigation under a dynamic scenario.In the method,we propose a local obstacle avoidance link to the maximum distance priority mechanism,on the basis of a simple learning mechanism,using an incremental hierarchical discriminant regression (IHDR)algorithm, and acquire environmental distance information with a laser range finder (LRF).This overcomes the over-de-pendence on the environmental model in traditional navigation methods,and simultaneously resolves the prob-lem of poor adaptive capacity in dynamic scene navigation with a simple learning-based mechanism,using the proposed local obstacle avoidance algorithm .We apply the proposed navigation method to an MT-R robot,and compare this with the experimental results from a learning-based navigation method.In addition,an algorithm analysis experiment is performed on LRF data using the proposed local obstacle avoidance algorithm.The results illustrate the feasibility of the proposed method,and reveal its effectiveperformance in dynamic scenarios.关键词
移动机器人/激光测距仪(LRF)/增量判别回归(IHDR)/学习机制/局部避障/导航方法Key words
mobile robot/laser range finder(LRF)/incremental hierarchical discriminant regression(IHDR)/learning mechanism/local obstacle avoidance/navigation method分类
信息技术与安全科学引用本文复制引用
张德龙,李威凌,吴怀宇,陈洋..基于学习机制的移动机器人动态场景自适应导航方法[J].信息与控制,2016,45(5):521-529,9.基金项目
国家自然科学基金资助项目（61203331，61573263）；湖北省科技支撑项目 （）
