XU Guozheng, GONG Weijie, ZHU Bo, GAO Xiang, SONG Aiguo, XU Baoguo. Interactive Control of Robotic Wheelchair Based on an Improved Head Pose Estimation Method[J]. ROBOT, 2018, 40(6): 878-886. DOI: 10.13973/j.cnki.robot.180104
Citation: XU Guozheng, GONG Weijie, ZHU Bo, GAO Xiang, SONG Aiguo, XU Baoguo. Interactive Control of Robotic Wheelchair Based on an Improved Head Pose Estimation Method[J]. ROBOT, 2018, 40(6): 878-886. DOI: 10.13973/j.cnki.robot.180104

Interactive Control of Robotic Wheelchair Based on an Improved Head Pose Estimation Method

  • As for the problem that the current iterative closet point (ICP) based head pose estimation method has more iterative steps and easily falls into local optimum while the random forest (RF) based head pose estimation method is of low accuracy and inferior stability, an improved head pose estimation method is proposed, and a real-time interactive control interface of robotic wheelchair based on the improved head pose estimation method is designed. Firstly, an improved head pose estimation method using ICP and RF algorithms is proposed based on the analyses on accuracy, real-time performance and stability issues existed in the current ICP and RF based head pose estimation algorithms. Then, the traditional robotic wheelchair joystick based head pose motion space mapping is built to achieve the seamless connections from the head pose estimation to the interactive control of robotic wheelchair. Finally, based on the performances analyses of the improved head pose estimation method using the standard head pose database, the robotic wheelchair platform is set up, and the movement trajectories are planned to verify the effectiveness of the proposed human-robot interactive interface using the improved head pose estimation method on the real-time control of robotic wheelchair. The experimental results demonstrate that the improved head pose estimation method has less iterative steps and can avoid falling into local optimum compared with the traditional ICP method, and the accuracy and stability of the proposed algorithm are better than the traditional RF method by increasing only a small amount of computation time. Moreover, the human-robot interactive interface using the improved head pose estimation method can control the robotic wheelchair following the predefined trajectories in a real-time and smooth manner.
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