Reseach On Multi-sensor Perception System Of Wearable Robot

With the continuous development of science and technology, Robots have been deeply used in our life. Especially the industry is entering the time of robot Manufacturing. Robot's efficiency, and high-precision action and high response speed can replace people from the heavy work. It can do the job that people can not do. In medical fields, The wearable walking assistant robot play an increasingly larger role as the assistant medical and rehabilitation patients.An exoskeleton robot is in combination with the robot technology and the body. The exoskeleton robot performs with the characteristics of high accuracy, fast response and "tireless", and it is likely to avoid the drawbacks of the traditional body weight supported treadmill training. Meanwhile, the exoskeleton robot will help to train the patients as well as record the training data, the exoskeleton robot has been a focus on the development of neuro-rehabilitation technique in the worldwide.This article analyzes walking movement of human body. Then article finds the simultaneous relationship between plantar pressure changes period and gait cycle. Using the angle sensors, accelerometers and force sensors to do one-dimensional position, velocity and power of the feedback signal.The achievements of this thesis are summarized as follows:(1) Design a wearable robot sensing system: We design the hardware system for the robot sensing system. The hardware is made up with the signal condition circuit and the signal acquisition, processing and transmission circuit. Also design a special one-dimensional force sensor to detect the force of putter.(2) Sensor data acquisition system design and achieve. The whole system is based on IPC. The software in PC is achieve by the VC++, can display data from time to time, and also can store the data. Finally, analyze the characteristics of various sensor signals and design different filter methods.(3) The experiments of the sensing system. The article through analyzing the testing data, verify the plantar pressure can react the characteristics gait cycle. By analyzing one-dimensional knee force sensor data to verify the wearable robot help boost results.The innovation of the paper is using the plantar pressure information to divide the gait cycle, using the changes of plantar pressure information as the Wearable Power Assist Robot control signals. Using the angle sensors, accelerometers and force sensors as one-dimensional position, velocity feedback signals.