Static forces weighted Jacobian motion models for improved Odometry

• Published in: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 169 - 175
• Main Authors: Hidalgo-Carrio, Javier, Babu, Ajish, Kirchner, Frank
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2014
• Subjects: Kinematics; Mathematical model; Mobile robots; Robot kinematics; Vectors; Wheels
• ISSN: 2153-0858; 2153-0866
• DOI: 10.1109/IROS.2014.6942557

The estimation of robot's motion at the prediction step of any localization framework is commonly performed using a motion model in conjunction with inertial measurements. In the context of field robotics, articulated mobile robots have complex chassis. They might require a complete model in comparison with the traditionally used planar assumption. In this paper, we use a Jacobian motion model-based approach for real-time inertial-aided odometry. The work makes use of the transformation approach [1] to accurately model 6-DoF kinematics. The algorithm relates normal forces with the probability of a contact-point to slip. The result increases the accuracy by weighting the least-squares solution using static forces prediction. The method is applied to the Asguard v3 system, a simple but highly capable leg-wheel hybrid robot. The performance of the approach is demonstrated in extensive field testing within different unstructured environments. In-depth error analysis and comparison with planar odometry is discussed, resulting in a more accurate localization.