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Data-Driven Analysis of Locomotion for a Class of Articulated Mobile Robots

Luca Carbonari, Andrea Botta, Paride Cavallone, Luigi Tagliavini, Giuseppe Quaglia

Year
2021
Citations
10

Abstract

Abstract In the recent past, the use of autonomous vehicles is becoming of relevant interest in several fields of application. In many cases, the use of articulated structures is preferred to single chassis robots for their peculiar modularity. Such vehicles are often built as an active front module and a rear one that is pulled passively or that can contribute to the vehicle traction when required. Understanding whether this contribution is convenient or not is the main matter of this paper. Two different mobile robots of different scales and purposes are taken into consideration. A dynamic model is presented and analyzed. An experimental validation of the model parameters is also presented in order to make it exploitable as a reliable analysis tool. At last, a simple yet effective actuation law is tested for both the considered robots to evaluate whether the contribution of the back module is beneficial or not to the whole machine maneuverability.

Keywords

ChassisRobotModularity (biology)Traction (geology)Mobile robotComputer scienceControl engineeringRobot locomotionSimulationArtificial intelligence

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