This paper presents a novel technique that allows for both computationally fast and sufficiently plausible simulation of vehicles with non-deformable tracks. The method is based on an effect we have called Contact Surface Motion. A comparison with several other methods for simulation of tracked vehicle dynamics is presented with the aim to evaluate methods that are available off-the-shelf or with minimum effort in general-purpose robotics simulators. The proposed method is implemented as a plugin for the open-source physics-based simulator Gazebo using the Open Dynamics Engine.
Mart ' i nez et al. @cite_12 define virtual points called (ICR), which depend on the desired turning radius and on a coefficient called . The robot follows a circular path centered at the ICR, and if the steering efficiency is equal to @math , the motion is the same as the motion of a geometrically equal differential-drive wheeled vehicle.
@cite_12
2027162577
In this paper we propose a kinematic approach for tracked mobile robots in order to improve motion control and pose estimation. Complex dynamics due to slippage and track-soil interactions make it difficult to predict the exact motion of the vehicle on the basis of track velocities. Nevertheless, real-time computations for autonomous navigation require an effective kinematics approximation without introducing dynamics in the loop. The proposed solution is based on the fact that the instantaneous centers of rotation (ICRs) of treads on the motion plane with respect to the vehicle are dynamics-dependent, but they lie within a bounded area. Thus, optimizing constant ICR positions for a particular terrain results in an approximate kinematic model for tracked mobile robots. Two different approaches are presented for off-line estimation of kinematic parameters: (i) simulation of the stationary response of the dynamic model for the whole velocity range of the vehicle; (ii) introduction of an experimental setup so that a genetic algorithm can produce the model from actual sensor readings. These methods have been evaluated for on-line odometric computations and low-level motion control with the Auriga-α mobile robot on a hard-surface flat soil at moderate speeds.