面向服务机器人的多行人检测与跟踪

服务机器人在给人提供帮助，带来生活便利的同时，需要检测并跟踪行人.然而，环境复杂，多个行人之间存在遮挡等问题，给行人的检测与跟踪带来了挑战.在行人检测方面，本文提出了最近邻方法融合激光人腿检测和Kinect人体检测的结果，有效改善了行人检测的精度和完整性.针对多行人跟踪，本文提出了一种改进的粒子滤波算法对行人的位置和速度进行了估计，克服了传统粒子滤波算法计算量大，重采样阶段粒子贫化的缺点.最后，在实际场景中采用改造的turtlebot机器人进行了测试，并进行了计算机可视化，实验结果证明本文提出的方法具有很好的准确性，实时性和鲁棒性.

Multi-People Detection and Tracking for Service Robots

Multi-people detection and tracking is a basic function for service robots when they serve people and interact with people. However, there exists a big challenge because of complex environment and occlusion of multiple people. To detect people, a new method based nearest neighbor algorithm combiningleg detection of laser and body detection of Kinect is proposed and it improves the accuracy and completeness of detection. For multi-people tracking, an improved particle filter is proposed to predict the people''s position and velocity, which can overcome the problem of heavy computational amount and particle degradation. In the experimental stage, a turtlebot robot with laser and Kinect is used to test the method in a real indoor environment. Results show the method can detect and track people in real time, and the method is robust and accurate.