Design and Experimental Validation of a Passive Following System for a Mecanum-Wheel Mobile Platform Based on Gimbal Posture Perception and Orthogonal Odometry Fusion

Indoor companion, rehabilitation, logistics, laboratory transport, and service robot scenarios require mobile platforms that can follow a human operator safely and flexibly under lighting changes, occlusion, texture-poor corridors, and dynamic pedestrian environments. Vision-, LiDAR-, and UWB-based following systems can provide high perception capability, but their deployment cost, environmental dependence, and sensing complexity remain limiting factors for low-perception-dependence applications. This paper presents a passive following system for a Mecanum-wheel mobile platform based on gimbal posture perception and orthogonal odometry fusion. A rope-tensioned two-axis gimbal is mounted above a 300 mm × 300 mm × 150 mm omnidirectional chassis, and a six-axis inertial sensor installed at the top of the gimbal detects pitch and roll changes induced by user traction. A piecewise posture-to-velocity mapping model with a dead zone, saturation, low-pass filtering, and acceleration limiting converts the user’s traction intention into planar velocity commands in the vehicle coordinate frame. To reduce pose errors caused by Mecanum-wheel slip and discontinuous roller-ground contact, two orthogonal passive odometry wheels and inertial attitude estimation are fused to provide planar position feedback for closed-loop following. A prototype was implemented using an Infineon TRAVEO CYT4BB77 controller, TI DRV8701E motor drivers, six-axis IMUs, magnetic encoders, and an embedded display interface. Experiments evaluated attitude estimation accuracy, planar localization accuracy, passive following performance, gyroscope compensation, and open-loop/closed-loop following. The compensated attitude module achieved a static yaw drift of 0.45 deg/h and a dynamic attitude RMSE below 0.56 deg. Orthogonal odometry fusion produced an average positioning error of 3.8 mm over a 3000 mm linear displacement, reducing error by approximately 84.6% compared with pure Mecanum-wheel drive odometry. In a 5000 mm forward traction task, closed-loop following reduced the average distance error from 38.6 mm to 11.5 mm compared with open-loop attitude mapping. The results indicate that the proposed gimbal-orthogonal odometry architecture provides a compact, intuitive, and environment-robust solution for passive following on omnidirectional mobile platforms.