TY - GEN
T1 - A caster-wheel-aware MPC-based motion planner for mobile robotics
AU - Arrizabalaga, Jon
AU - Van Duijkeren, Niels
AU - Ryll, Markus
AU - Lange, Ralph
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Differential drive mobile robots often use one or more caster wheels for balance. Caster wheels are appreciated for their ability to turn in any direction almost on the spot, allowing the robot to do the same and thereby greatly simplifying the motion planning and control. However, in aligning the caster wheels to the intended direction of motion they produce a so-called bore torque. As a result, additional motor torque is required to move the robot, which may in some cases exceed the motor capacity or compromise the motion planner's accuracy. Instead of taking a decoupled approach, where the navigation and disturbance rejection algorithms are separated, we propose to embed the caster wheel awareness into the motion planner. To do so, we present a caster-wheel-aware term that is compatible with MPC-based control methods, leveraging the existence of caster wheels in the motion planning stage. As a proof of concept, this term is combined with a model-predictive trajectory tracking controller. Since this method requires knowledge of the caster wheel angle and rolling speed, an observer that estimates these states is also presented. The efficacy of the approach is shown in experiments on an intralogistics robot and compared against a decoupled bore-torque reduction approach and a caster-wheel agnostic controller. Moreover, the experiments show that the presented caster wheel estimator performs sufficiently well and therefore avoids the need for additional sensors. Video: https://youtu.be/NXXZKEZUi30
AB - Differential drive mobile robots often use one or more caster wheels for balance. Caster wheels are appreciated for their ability to turn in any direction almost on the spot, allowing the robot to do the same and thereby greatly simplifying the motion planning and control. However, in aligning the caster wheels to the intended direction of motion they produce a so-called bore torque. As a result, additional motor torque is required to move the robot, which may in some cases exceed the motor capacity or compromise the motion planner's accuracy. Instead of taking a decoupled approach, where the navigation and disturbance rejection algorithms are separated, we propose to embed the caster wheel awareness into the motion planner. To do so, we present a caster-wheel-aware term that is compatible with MPC-based control methods, leveraging the existence of caster wheels in the motion planning stage. As a proof of concept, this term is combined with a model-predictive trajectory tracking controller. Since this method requires knowledge of the caster wheel angle and rolling speed, an observer that estimates these states is also presented. The efficacy of the approach is shown in experiments on an intralogistics robot and compared against a decoupled bore-torque reduction approach and a caster-wheel agnostic controller. Moreover, the experiments show that the presented caster wheel estimator performs sufficiently well and therefore avoids the need for additional sensors. Video: https://youtu.be/NXXZKEZUi30
UR - http://www.scopus.com/inward/record.url?scp=85124702874&partnerID=8YFLogxK
U2 - 10.1109/ICAR53236.2021.9659478
DO - 10.1109/ICAR53236.2021.9659478
M3 - Conference contribution
AN - SCOPUS:85124702874
T3 - 2021 20th International Conference on Advanced Robotics, ICAR 2021
SP - 613
EP - 618
BT - 2021 20th International Conference on Advanced Robotics, ICAR 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th International Conference on Advanced Robotics, ICAR 2021
Y2 - 6 December 2021 through 10 December 2021
ER -