TY - JOUR
T1 - Unwieldy Object Delivery With Nonholonomic Mobile Base
T2 - A Stable Pushing Approach
AU - Tang, Yujie
AU - Zhu, Hai
AU - Potters, Susan
AU - Wisse, Martijn
AU - Pan, Wei
PY - 2023
Y1 - 2023
N2 - This letter addresses the problem of pushing manipulation with nonholonomic mobile robots. Pushing is a fundamental skill that enables robots to move unwieldy objects that cannot be grasped. We propose a stable pushing method that maintains stiff contact between the robot and the object to avoid consuming repositioning actions. We prove that a line contact, rather than a single point contact, is necessary for nonholonomic robots to achieve stable pushing. We also show that the stable pushing constraint and the nonholonomic constraint of the robot can be simplified as a concise linear motion constraint. Then the pushing planning problem can be formulated as a constrained optimization problem using nonlinear model predictive control (NMPC). According to the experiments, our NMPC-based planner outperforms a reactive pushing strategy in terms of efficiency, reducing the robot's traveled distance by 23.8% and time by 77.4%. Furthermore, our method requires four fewer hyperparameters and decision variables than the Linear Time-Varying (LTV) MPC approach, making it easier to implement. Real-world experiments are carried out to validate the proposed method with two differential-drive robots, Husky and Boxer, under different friction conditions.
AB - This letter addresses the problem of pushing manipulation with nonholonomic mobile robots. Pushing is a fundamental skill that enables robots to move unwieldy objects that cannot be grasped. We propose a stable pushing method that maintains stiff contact between the robot and the object to avoid consuming repositioning actions. We prove that a line contact, rather than a single point contact, is necessary for nonholonomic robots to achieve stable pushing. We also show that the stable pushing constraint and the nonholonomic constraint of the robot can be simplified as a concise linear motion constraint. Then the pushing planning problem can be formulated as a constrained optimization problem using nonlinear model predictive control (NMPC). According to the experiments, our NMPC-based planner outperforms a reactive pushing strategy in terms of efficiency, reducing the robot's traveled distance by 23.8% and time by 77.4%. Furthermore, our method requires four fewer hyperparameters and decision variables than the Linear Time-Varying (LTV) MPC approach, making it easier to implement. Real-world experiments are carried out to validate the proposed method with two differential-drive robots, Husky and Boxer, under different friction conditions.
KW - Contact modeling
KW - manipulation planning
UR - http://www.scopus.com/inward/record.url?scp=85174802446&partnerID=8YFLogxK
U2 - 10.1109/LRA.2023.3322323
DO - 10.1109/LRA.2023.3322323
M3 - Article
AN - SCOPUS:85174802446
SN - 2377-3766
VL - 8
SP - 7727
EP - 7734
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 11
ER -