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
2065833720 2027162577 2101895037 1985690111
This paper addresses the path following control problem of wheeled mobile robots in the presence of wheel skidding and slipping. A conditional global positioning system (GPS)-based path following controller is proposed for four generic WMRs to achieve high-precision path following performance. The proposed controller utilizes real-time kinematic-GPS and other aiding sensors to determine the robot's pose and wheel skidding and slipping perturbations to achieve accurate path following control. The reported simulation and experimental results suggest that with this control scheme, the WMRs are able to maneuver with precision. © 2009 Wiley Periodicals, Inc. 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. This paper describes experiments regarding navigation performance using a new locomotion interface for walking through virtual space. Although traveling on foot is the most intuitive style of locomotion, proprioceptive feedback from walking is not provided in most applications of virtual environments. We developed an infinite surface driven by actuators for enabling a sense of walking. Torus-shaped surfaces are selected to realize the locomotion interface. The device employs twelve sets of treadmills, connected side by side and driven in perpendicular directions. The virtual infinite surface is generated by the motion of the treadmills. A walker can go in any direction while his her position is fixed in the real world. The device is called a Torus Treadmill. Navigation performance was measured by path-reproduction tests. Subjects were immersed in a virtual grass-covered plain on which a cone-shaped target object was placed. The subjects first traveled to the target object. After they reached it, the target object disappeared and the rehomed subjects were asked to return to the place where the target object was placed. We also set two target objects, and the subject traveled along a bent path. We compared two locomotion modes: walking on the Torus Treadmill and moving purely by joystick operation. The results of the bent-path experiment showed that the accuracy of the path reproduction in the Torus Treadmill mode is better than that of joystick mode. This article presents a new kind of navigation system for agricultural machines. The focus is on trajectory control where a Nonlinear Model Predictive path tracking for tractor and trailer system is presented. The experiments of the proposed method are carried out by using real agricultural machines in real environments. The agricultural objective is to drive so that swaths are exactly side-by-side, without overlapping or gaps. Hence, the objective of this research was to control the lateral position of the towed implement and to keep it close to the adjacent driving line. The adjacent driving line was recognized locally by using a 2D laser scanner. The local measurement and global position information was merged with the help of an Extended Kalman Filter (EKF). The measurement of the heading by GPS was improved by using an inertial measurement unit and a separate EKF filter. The position of the implement was controlled by steering the tractor and by the use of a hydraulically controlled joint. Because there were two actuators which affected the position of the implement, the problem was a multivariable control problem. Nonlinear Model Predictive Control (NMPC) was used to accomplish the navigation task. The goal was to build a system, which is able to have at least the same accuracy as a human driver. The sufficient accuracy requirement was at most 10cm lateral error at a speed of 12km h. The results presented in the article show that the goal was met and NMPC is a feasible method for accurate path tracking. Further investigation is, however, needed to adapt the method to other kinds of agricultural machines.