@conference {Tu2022,
	title = {FreeSN: A Freeform Strut-node Structured Modular Self-reconfigurable Robot - Design and Implementation},
	booktitle = {2022 International Conference on Robotics and Automation (ICRA)},
	year = {2022},
	pages = {4239{\textendash}4245},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Philadelphia, PA, USA},
	abstract = {This paper proposes a novel freeform strut-node structured modular self-reconfigurable robot (MSRR) called FreeSN, consisting of strut and node modules. A node module is mainly a low-carbon steel spherical shell. A strut module contains two freeform connectors, which provide strong magnetic connections and flexible spherical motions. The FreeSN system shares the benefits of freeform connection and strut-node structures. The freeform connection brings good adaptability to the environment. The triangle substructures inside the system configuration significantly improve the structural stability. The parallel execution of module motions can superpose the module capabilities and makes the system more scalable. The modules can combine these robot features by selecting the system configuration and better fit different circumstances and tasks. Four demonstrations, including assembly, obstacle crossing, transportation, and object manipulation, are designed to show the capabilities of the FreeSN system in different aspects. The results show the great performance and versatility of this MSRR system.},
	keywords = {Automation, Connectors, Robots, Steel, Structural engineering, Task analysis, Transportation},
	isbn = {978-1-7281-9682-4},
	doi = {10.1109/ICRA46639.2022.9811583},
	author = {Yuxiao Tu and Guanqi Liang and Tin Lun Lam}
}
@conference {Tu2021,
	title = {Graph Convolutional Network based Configuration Detection for Freeform Modular Robot Using Magnetic Sensor Array},
	booktitle = {2021 IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2021},
	pages = {4252{\textendash}4258},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Xi{\textquoteright}an, China},
	abstract = {Modular self-reconfigurable robotic (MSRR) systems are potentially more robust and more adaptive than conventional systems. Following our previous work where we proposed a freeform MSRR module called FreeBOT, this paper presents a novel configuration detection system for FreeBOT using a magnetic sensor array. A FreeBOT module can be connected by up to 11 modules, and the proposed configuration detection system can locate a variable number of connection points accurately in real-time. By equipping FreeBOT with 24 magnetic sensors, the magnetic field density produced by magnets and steel spherical shells can be monitored. The connectable area is split into 199 non-uniform regions, including 84 uniform regions. Using a Graph Convolutional Network (GCN) based algorithm, the connection points can be located accurately under ferromagnetic environments. The system can locate a variable number of connection points for such a region division with only single connection point training data. Finally, the localization algorithm can run faster than 40 Hz on FreeBOT. With the real-time configuration detection system, the FreeBOT system has the potential to reconfigure automatically and accurately.},
	keywords = {Conferences, Location awareness, Magnetic sensors, Real-time systems, Robot sensing systems, Steel, Training data},
	isbn = {978-1-7281-9078-5},
	issn = {1050-4729},
	doi = {10.1109/ICRA48506.2021.9561340},
	author = {Yuxiao Tu and Guanqi Liang and Tin Lun Lam}
}
