@conference {Zhang2021,
	title = {Task-Space Decomposed Motion Planning Framework for Multi-Robot Loco-Manipulation},
	booktitle = {2021 IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2021},
	pages = {8158{\textendash}8164},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Xi{\textquoteright}an, China},
	abstract = {This paper introduces a novel task-space decomposed motion planning framework for multi-robot simultaneous locomotion and manipulation. When several manipulators hold an object, closed-chain kinematic constraints are formed, and it will make the motion planning problems challenging by inducing lower-dimensional singularities. Unfortunately, the constrained manifold will be even more complicated when the manipulators are equipped with mobile bases. We address the problem by introducing a dual-resolution motion planning framework which utilizes a convex task region decomposition method, with each resolution tuned to efficient computation for their respective roles. Concretely, this dual-resolution approach enables a global planner to explore the low-dimensional decomposed task-space regions toward the goal, then a local planner computes a path in high-dimensional constrained configuration space. We demonstrate the proposed method in several simulations, where the robot team transports the object toward the goal in the obstacle-rich environments.},
	keywords = {Computational modeling, Conferences, Kinematics, Manifolds, Manipulators, Planning, System recovery},
	isbn = {978-1-7281-9078-5},
	issn = {1050-4729},
	doi = {10.1109/ICRA48506.2021.9560902},
	author = {Xiaoyu Zhang and Lei Yan and Tin Lun Lam and Sethu Vijayakumar}
}
