预测行人运动的服务机器人POMDP 导航

为提高室内动态环境下服务机器人对行人的自然避让能力，对人的运动轨迹模式进行建模，在此基础上引入了将行人运动长、短期预测结合起来的方法．为适应传感器噪声及网络延迟等因素所造成的感知—控制回路中的多源不确定性，将人与机器人的相对位置关系建模为部分可观的马尔可夫状态．采用部分可观的马尔可夫决策过程（POMDP）进行多源不确定性下的概率决策，协调控制机器人全局路径规划、反应式运动及速度控制等行为模块．实验结果验证，它能够实现提前避碰的安全导航，因避免反复的曲折与徘徊运动而提高了机器人导航效率．

POMDP Navigation of Service Robots with Human Motion Prediction

To improve the natural pedestrian-avoidance skills of service robots in indoor dynamic environments,a method of combining long-term and short-term prediction of pedestrian's motion is introduced on the basis of modeling humans' motion trajectory patterns.In order to accommodate the uncertainties in the perception-control loop of robots,which are mainly caused by sensor noise and time delay in network and other factors,the relative position relation between human and robot is modeled as partially observable ...