TY - GEN
T1 - Motion planning for 4WS vehicle with autonomous selection of steering modes via an MIQP-MPC controller
AU - Nguyen, Ngoc Thinh
AU - Gangavarapu, Pranav Tej
AU - Mandel, Nicolas
AU - Bruder, Ralf
AU - Ernst, Floris
N1 - Publisher Copyright:
© 2024 IEEE.
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PY - 2024
Y1 - 2024
N2 - Navigation in agricultural fields imposes various constraints on manoeuvrability, which can be tackled by using four-wheel steering (4WS) vehicles which are capable of switching between multiple steering mechanisms with distinct kinematic properties. For example, parallel positive steering (PPS) with four wheels in parallel to each other can maintain the vehicle's heading when moving along a curve. Symmetric negative steering (SNS) with two wheels on each side sharing the same steering angle can turn with a small radius. This paper presents a controller capable of selecting and switching between the two aforementioned modes autonomously for better trajectory tracking performance with special heading requirements for agricultural applications. The controller is implemented as a Model Predictive Control (MPC) controller formulated as a mixed-integer quadratic programming (MIQP) problem for the 4WS vehicle. Practical constraints, such as limits on wheel velocities, steering angles and their rate-of-changes are taken into account. A Python implementation confirms the real-time execution capability of the controller and simulation results highlight its effectiveness.
AB - Navigation in agricultural fields imposes various constraints on manoeuvrability, which can be tackled by using four-wheel steering (4WS) vehicles which are capable of switching between multiple steering mechanisms with distinct kinematic properties. For example, parallel positive steering (PPS) with four wheels in parallel to each other can maintain the vehicle's heading when moving along a curve. Symmetric negative steering (SNS) with two wheels on each side sharing the same steering angle can turn with a small radius. This paper presents a controller capable of selecting and switching between the two aforementioned modes autonomously for better trajectory tracking performance with special heading requirements for agricultural applications. The controller is implemented as a Model Predictive Control (MPC) controller formulated as a mixed-integer quadratic programming (MIQP) problem for the 4WS vehicle. Practical constraints, such as limits on wheel velocities, steering angles and their rate-of-changes are taken into account. A Python implementation confirms the real-time execution capability of the controller and simulation results highlight its effectiveness.
UR - https://www.mendeley.com/catalogue/528aae7c-8115-39b4-9a99-f7c696596b86/
U2 - 10.1109/ICRA57147.2024.10610461
DO - 10.1109/ICRA57147.2024.10610461
M3 - Conference contribution
SN - 979-8-3503-8458-1
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 9765
EP - 9771
BT - 2024 IEEE International Conference on Robotics and Automation (ICRA)
PB - IEEE
CY - Yokohama, Japan
ER -
