By Ramón González, Francisco Rodríguez, José Luis Guzmán
This monograph is framed in the context of off-road cellular robotics. specifically, it discusses concerns concerning modelling, localization, and movement regulate of tracked cellular robots operating in planar slippery stipulations. Tracked locomotion constitutes a widely known resolution for cellular systems working over diversified not easy terrains, consequently, tracked robotics constitutes a tremendous examine box with many purposes (e.g. agriculture, mining, seek and rescue operations, army activities). the categorical themes of this monograph are: ancient point of view of tracked autos and tracked robots; trajectory-tracking version bearing in mind slip influence; visual-odometry-based localization innovations; and complicated slip-compensation movement controllers making sure effective real-time execution. actual experiments with a true tracked robotic are offered exhibiting the higher functionality of the recommended novel ways to identified suggestions.
key words: longitudinal slip, visible odometry, slip-compensation keep an eye on, powerful predictive keep watch over, trajectory tracking.
comparable topics: Robotics – Mechanical Engineering – Mechanics – computing device technology – synthetic Intelligence - Applications
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Additional info for Autonomous Tracked Robots in Planar Off-Road Conditions: Modelling, Localization, and Motion Control
It compares the current pixel displacement with the previous ones, if the diﬀerence is greater than a threshold, then the current value is considered as an outlier. In this way, these peaks or outliers, due to false matches, are partially compensated. As shown in the following subsection, this ﬁlter works properly, and it requires a small computation time. 3 Results 49 Fig. 2 Localization Strategies Validation In this subsection, the physical experiments validating the localization approach presented in this chapter are discussed.
5. 8). 6. 13). 7. 14). 8. Repeat from step 1. 5 Computational Aspects of Template Matching This subsection discusses some experiments carried out to select the most appropriate template/search area size for a satisfactory performance of the correlation algorithm and the employed computation time. The main drawback of template matching approach is its computation cost, since the template has to be slid over the whole search area. 2 Localization Using Visual Odometry 45 by means of a matching process is O = m2 (n − m + 1)2 .
In the work , slip is estimated using a Kalman ﬁlter combining information from an Inertial Navigation System (INS) and laser scanner sensors. An Extended Kalman Filter (EKF) combining IMU, GPS and wheel encoder measurements is proposed in . In , the authors use the diﬀerence between position measured by GPS and foreseen position computed from kinematic model to estimate slip. For a review of more slip estimation strategies see . In this book, a ﬁrst solution was to measure the angular velocity of the tracks using encoders and the robot forward velocity using a Doppler radar.
Autonomous Tracked Robots in Planar Off-Road Conditions: Modelling, Localization, and Motion Control by Ramón González, Francisco Rodríguez, José Luis Guzmán