@conference {Zhao2022,
	title = {SnailBot: A Continuously Dockable Modular Self-reconfigurable Robot Using Rocker-bogie Suspension},
	booktitle = {2022 International Conference on Robotics and Automation (ICRA)},
	year = {2022},
	pages = {4261{\textendash}4267},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Philadelphia, PA, USA},
	abstract = {This paper proposes a novel modular self-assembling, self-reconfiguring robot with the 3D continuous dock called {\textquotedblleft}SnailBot{\textquotedblright}. SnailBot mainly consists of a spherical ferromagnetic shell and a six-wheel rocker chassis with embedded magnets. Unlike many other existing modular self-reconfigurable robots with fixed docking locations, SnailBot uses the 3D continuous dock to attach to its peers regardless of alignment. This freeform docking mechanism can greatly improve the efficiency of self-reconfiguration and reduce docking failures because there is nearly no constraint in the location of the connector. Compared with the existing freeform MSRR, SnailBot can form a more structurally stable connection to its peers without loss of connection efficiency. Owing to the excellent obstacle crossing ability of the rocker-bogie suspension, the robot can freely crawl on other modules in the form of a sliding sphere. Experiments demonstrate the basic actions of a single module and some applications of SnailBots, such as a manipulator.},
	keywords = {Automation, Connectors, Manipulators, Three-dimensional displays},
	isbn = {978-1-7281-9682-4},
	doi = {10.1109/ICRA46639.2022.9811779},
	author = {Da Zhao and Tin Lun Lam}
}
@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}
}
