Abstract
In recent years, as the mechanical structure of humanoid robots increasingly resembles the human form, research on pedestrian navigation technology has become of great significance for the development of humanoid robot navigation systems. To solve the problem that the wearable inertial navigation system based on micro-inertial measurement units (MIMUs) installed on feet cannot effectively realize its positioning function when the body movement is too drastic to be measured correctly by commercial grade inertial sensors, a pedestrian navigation method based on construction of a virtual inertial measurement unit (VIMU) and gait feature assistance is proposed. The inertial data from different positions of pedestrians’ lower limbs are collected synchronously via actual IMUs as training samples. The nonlinear mapping relationship between inertial information from the human foot and leg is established by a visual geometry group-long short term memory (VGG-LSTM) neural network model, based on which the foot VIMU and virtual inertial navigation system (VINS) are constructed. The VINS experimental results show that, combined with zero-velocity update (ZUPT), the integrated method of error modification proposed in this paper can effectively reduce the accumulation of positioning errors in situations where the gait type exceeds the measurement range of the inertial sensors. The positioning performance of the proposed method is more accurate and stable in complex gait types than that merely using ZUPT.
Highlights
Pedestrian navigation systems, with their light weight, small size, cheap price, and convenience to carry, show wide prospects in military and civilian application
Aboelmagd [17] proposed a global positioning system/ inertial navigation systems (GPS/INS) integrated navigation technology based on input delay neural network (IDNN), and the results showed that IDNN method showed better navigation performance than the GPS/INS integrated navigation system based on Kalman filter when
Inspired by the research works on NN mentioned above, a novel pedestrian navigation method based on gait feature assistance and construction of a virtual foot IMU is proposed
Summary
Pedestrian navigation systems, with their light weight, small size, cheap price, and convenience to carry, show wide prospects in military and civilian application. The PDR algorithm needs to conduct kinematic modeling of human body, calculate the step length according to parameters such as step frequency and leg length, and obtain the 3D pedestrian position information with the aid of magnetic sensors. Inspired by the research works on NN mentioned above, a novel pedestrian navigation method based on gait feature assistance and construction of a virtual foot IMU is proposed. It can be learned from previous experience that inertial sensors can be installed on the human hand, waist, shoulders and other parts, where there are periodic changes during walking.
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