Who Are We?
Established in 2019 and directed by Prof. Tin Lun LAM, the research group is committed to collaborating with leading international experts to research leading-edge robotic technologies to give impetus to the application of the technologies in new fields, popularizing the knowledge of robotics and AI to society, and strives to build a Shenzhen-based world-class robotics research and application promotion hub.
The research group has strong talents who have long been engaged in Robotics and AI research. Most scientific research outputs were published in top-tier international journals and conference proceedings in Robotics and AI, such as TPAMI, TIP, TNNLS, TCSVT, T-RO, TMECH, RA-L, JFR, ICRA, and IROS. One of the research achievements, “FreeBOT: A Freeform Modular Self-reconfigurable Robot with Arbitrary Connection Point,” won the IROS Robot Mechanism and Design Best Paper Award in 2020, and it has also been reported by many internationally renowned media, including IEEE Spectrum, Engadget, and NHK.
Our Research Focus
The vision of the Freeform Robotics Research Group is to develop a general-purpose robotic swarm that can physically be connected to form any shape with different functionalities according to the environment and task. It will initiate a revolutionary way of the robotic system’s realization. The impact on the robotic society is comparable to the revolutionary impact of additive manufacturing technology on traditional processing industries. To realize this, several fundamental technical challenges are summarized as follows:
Cognition: Self-carried relative localization; Time/viewpoint-variant data fusion; Multi-robot SLAM
Decision: Multi-task/agent planning in uncertain and dynamic environments; Optimal task-configuration matching;
Implementation: Flexible and robust connection mechanism; Decentralized control;
Most of the listed technical challenges also apply to the existing multi-robot systems.
Keywords: Multi-robot systems; self-reconfigurable robots; modular robots; multi-robot environment perception (SLAM); multi-robot relative positioning; multi-robot manipulation; multi-robot multi-task planning; swarm intelligence; decentralized control.