摘要
针对深海底履带机器车的未知、复杂工作环境,提出一种履带机器车导航和避障算法。该算法先用声纳传感器实时检测障碍物的位置,再用D-S理论推算出障碍物的更准确位置,然后运用改进势场法进行行走方向决策,规划出履带机器车的作业路径,实现对深海履带机器车的导航和避障。仿真和试验结果表明,此算法适应于动态未知复杂环境下的深海履带机器车实时导航和避障,且在目标附近存在障碍物时也能达到目标。
A real-time navigation and obstacle avoidance method was presented for deep-seabed tracked vehicle in unknown and complex environment. The position of obstacles was firstly detected by sonar sensors for this method, and then Dempster-Shafer theory was used to calculate more accuracy position of obstacles. Lastly, the moving direction of tracked vehicle was decided by improved artificial potential field and the working path was planned in time. So, navigation and obstacle avoidance for tracked vehicle was realized. This method is valid in complex and dynamic environment, which can also overcome the problem of unreachable goals near the obstacles. The effectiveness of this method is verified by simulation and experiment results.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2007年第1期128-132,共5页
Journal of Central South University:Science and Technology
基金
国际海底区域研究开发"十五"项目(DY105-03-02-06)
国家重点基础研究发展规划项(2002CB312203)
国家自然科学基金资助项目(60505018)
作者简介
王随平（1956-），湖南长沙人，教授，从事人工智能、深海机器人、现场总线以及计算机控制系统研究;通讯作者：王随平，男，教授：电话：0731-8836475（O）;E—mail：wangsp@mail．csu．edu．cn
