Abstract
Odometry is a simple and practical method that provides a periodic real-time estimation of the relative displacement of a mobile robot based on the measurement of the angular rotational speed of its wheels. The main disadvantage of odometry is its unbounded accumulation of errors, a factor that reduces the accuracy of the estimation of the absolute position and orientation of a mobile robot. This paper proposes a general procedure to evaluate and correct the systematic odometry errors of a human-sized three-wheeled omnidirectional mobile robot designed as a versatile personal assistant tool. The correction procedure is based on the definition of 36 individual calibration trajectories which together depict a flower-shaped figure, on the measurement of the odometry and ground truth trajectory of each calibration trajectory, and on the application of several strategies to iteratively adjust the effective value of the kinematic parameters of the mobile robot in order to match the estimated final position from these two trajectories. The results have shown an average improvement of 82.14% in the estimation of the final position and orientation of the mobile robot. Therefore, these results can be used for odometry calibration during the manufacturing of human-sized three-wheeled omnidirectional mobile robots.
Highlights
Borenstein et al [2] reviewed the most relevant mobile robot relative positioning methods based on internal data gathered by the mobile robot: odometry and inertial navigation, and the most relevant absolute positioning methods based on gathering external surrounding data
Odometry is usually defined as a relative positioning method that uses the measures of the velocities of the wheels to estimate the position of the robot
The trajectory estimated with the odometry is based on relative onboard information that is prone to cumulative systematic errors while the ground truth trajectory estimated with the precise onboard LIDAR is based on an absolute description of the structured environment around the mobile robot that is not prone to systematic errors
Summary
Mobile robots have a huge range of potential applications in industrial, office and home environments. This new method consists of: (1) creating a model of the virtual robot and of the systematic errors; (2) performing simulation tests with the virtual robot; (3) performing experimental tests with a real robot; (4) comparing both results to estimate the EPKs and redefine the Jacobian matrix of the mobile robot In this case, the simulation and experimental tests consist of two robot translations along straight paths and one rotation about itself, and the calculated EPKs are used to correct the angular velocities of the wheels. The new contribution of this paper is the proposal of a combination of 36 straight and curved calibration trajectories for systematic odometry error evaluation and correction in a three-wheeled omnidirectional mobile robot This procedure has been empirically applied and validated in a real human-sized three-wheeled omnidirectional mobile robot of 1.760 m and 30 kg (Figure 1). These two minimization methods will be applied to calibrate the odometry of the mobile robot
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