4.6 Article

Distributed Tube-Based Nonlinear MPC for Motion Control of Skid-Steer Robots With Terra-Mechanical Constraints

Journal

IEEE ROBOTICS AND AUTOMATION LETTERS
Volume 6, Issue 4, Pages 8045-8052

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2021.3102328

Keywords

Motion control; distributed robot systems; robust control; mining robotics; field robots

Categories

Funding

  1. Beca Postdoctorado Escuela de Ingenieria, Pontificia Universidad Catolica de Chile
  2. CORFO Engineering 2030 [14ENI2-26 862]
  3. FONDECYT [1171760]
  4. ANID Fondecyt [1201319]
  5. ANID [FB0008]

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The study introduces an integrated control architecture based on distributed tube-based nonlinear Model Predictive Control and adaptive model-based control for field robots, aiming to enhance navigation and motion control by reducing tire slippage and sideward sliding. Experimentation on an industrial loader under off-road conditions showed that the proposed approach significantly decreased tire slip and sideways sliding, as well as reducing lateral and longitudinal trajectory tracking errors.
Strategies to reduce slippage and disturbing wheelterrain interactions are essential to improve navigation and motion control of field robots. Thus, this work proposes an integral control architecture based on a distributed tube-based nonlinear Model Predictive Control scheme to regulate tire dynamics and an adaptive model-based control scheme for trajectory tracking over deformable terrain. For the proposed control architecture, the overall system is decomposed into simpler subsystems to separately represent the four-tire driven motion dynamics (i.e., slip and sideslip) from that of the vehicle's pose and speeds. Since a vehicle and its tires have different dynamic response characteristics, cooperative agents of the distributed control strategy are able to exchange information between subsystems to attain evenly allocated drivetrain torques during slippery situations. The motion controller is made adaptive to terra-mechanical parameters with a NonlinearMoving Horizon Estimation approach working under a parallel Real-Time Iteration scheme. Field experimentations in an industrial compact loader Cat degrees 262 C subject to off-road conditions demonstrated that the proposed approach was capable of reducing up to a minimum of 18.2% of tire slip and sidelip range of +/- 6.6 degrees when compared to its non-robust counterpart. Consequently, the proposed approach was also able to reduce lateral and longitudinal trajectory tracking errors by around 66.6% and 43.7%, respectively, which may have a direct impact on the resources of the machinery.

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