摘要
针对真实水流环境下的水下机器人化学羽状物追踪问题,参考生物嗅觉定位原理,提出化学羽状物源头概率分布地图的绘制算法和水下机器人搜索羽状物源头的路径规划策略,提高了机器人搜索羽状物源头的效率以及准确性。化学羽状物在流场中释放后,水下机器人采集在搜索区域内探测到的流场和羽状物的信息,利用贝叶斯理论描述出羽状物在空间和时间上的变化,绘制出羽状物源头概率分布地图,通过人工势场法规划出一个最优的搜索轨迹,达到羽状物探测概率的最大化,水下机器人能够沿规划路径跟踪羽状物直到发现羽状物源头。通过真实水流环境下进行的机器人追踪实验结果验证了该规划策略的可行性。
To solve the problem of underwater vehicle searching chemical plume in real water environment,and based on biological olfactory positioning principle,efficiency and accuracy of searching was improved. a probability distribution map was built and a kind of path planning strategy was proposed.According to the flow field and plume information which were detected by vehicle in its searching area after chemical plume was released,trend of chemical plume in time and space was described based on Bayesian theory. And best search track was planned based on artificial potential field（ ATF） method.The underwater vehicle can search along the tracking path above until found the plume source. Through tracing experiments in real water flow environment,the result was good and the feasibility of the tracing path was verified.
出处
《电机与控制学报》
EI
CSCD
北大核心
2016年第1期110-118,共9页
Electric Machines and Control
基金
国家自然科学基金(61175095)
关键词
水下机器人
嗅觉定位
羽状物跟踪
贝叶斯理论
人工势场
underwater vehicle
biological olfactory location
plume track
Bayesian theory
artificial potential field
