@article {Luo2022,
	title = {Adaptive Flow Planning of Modular Spherical Robot Considering Static Gravity Stability},
	journal = {IEEE Robotics and Automation Letters},
	volume = {7},
	year = {2022},
	pages = {4228{\textendash}4235},
	publisher = {IEEE},
	abstract = {Modular robots have a unique obstacle-crossing method, flow. Flow is realized by constantly changing the connection relationship between modules, namely reconfiguration. Existing flow planning methods do not consider the static stability in their adaptation to obstacles. This letter proposes a flow planning method with scalability, adaptability, and static gravity stability. The criterion of static gravity stability is always satisfied through the following two innovations. First, each target configuration in the flow process is designed to grasp obstacles like vines. Second, in motion planning, each module maintains contact with the obstacle or a fixed module to maximize the supporting polygon of the configuration. What{\textquoteright}s more, the simplified path output by the connection planning and the precise calculation based on the mesh model realize the scalability and adaptability of the flow planning method. In simulation, we evaluate the adaptability to various obstacles and the margin of static gravity stability.},
	keywords = {Cellular and modular robots, Gravity, Hardware, path planning for multiple mobile robots or agents, Planning, Robot kinematics, Robots, scheduling and coordination, Stability criteria, Three-dimensional displays},
	issn = {2377-3774},
	doi = {10.1109/LRA.2022.3150028},
	author = {Haobo Luo and Tin Lun Lam}
}
@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}
}
@article {Guo2021,
	title = {Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment},
	journal = {IEEE Robotics and Automation Letters},
	volume = {6},
	year = {2021},
	pages = {8349{\textendash}8356},
	publisher = {IEEE},
	abstract = {The core problem of visual multi-robot simultaneous localization and mapping (MR-SLAM) is how to efficiently and accurately perform multi-robot global localization (MR-GL). The difficulties are two-fold. The first is the difficulty of global localization for significant viewpoint difference. Appearance-based localization methods tend to fail under large viewpoint changes. Recently, semantic graphs have been utilized to overcome the viewpoint variation problem. However, the methods are highly time-consuming, especially in large-scale environments. This leads to the second difficulty, which is how to perform real-time global localization. In this letter, we propose a semantic histogram based graph matching method that is robust to viewpoint variation and can achieve real-time global localization. Based on that, we develop a system that can accurately and efficiently perform MR-GL for both homogeneous and heterogeneous robots. The experimental results show that our approach is about 30 times faster than Random Walk based semantic descriptors. Moreover, it achieves an accuracy of 95\% for global localization, while the accuracy of the state-of-the-art method is 85\%.},
	keywords = {Global localization, Histograms, large viewpoint difference, Location awareness, multi-robot map merging, Real-time systems, semantic SLAM, Semantics, Simultaneous localization and mapping, Three-dimensional displays, Visualization},
	issn = {2377-3774},
	doi = {10.1109/LRA.2021.3058935},
	author = {Xiyue Guo and Junjie Hu and Junfeng Chen and Fuqin Deng and Tin Lun Lam}
}
@conference {36,
	title = {Coverage search in 3D},
	year = {2013},
	address = {Linkoeping, Sweden},
	abstract = {Searching with a sensor for objects and to observe parts of a known environment efficiently is a fundamental problem in many real-world robotic applications such as household robots searching for objects, inspection robots searching for leaking pipelines, and rescue robots searching for survivors after a disaster. We consider the problem of identifying and planning efficient view point sequences for covering complex 3d environments. We compare empirically several variants of our algorithm that allow to trade-off schedule computation against execution time. Our results demonstrate that, despite the intractability of the overall problem, computing effective solutions for coverage search in real 3d environments is feasible.},
	keywords = {3D environments, coverage search, Educational institutions, execution time, household robots, image sequences, inspection robots, leaking pipelines search, objects search, path planning, Planning, rescue robots, Robot sensing systems, robot vision, robotic applications, schedule computation, Search problems, sensor, service robots, solid modelling, survivors search, Three-dimensional displays, Traveling salesman problems, view point sequences},
	doi = {10.1109/SSRR.2013.6719340},
	author = {Dornhege, C. and Kleiner, A. and Kolling, A.}
}
@conference {37,
	title = {Coverage search in 3D},
	booktitle = {Proc. of the {IEEE} Int. Workshop on Safety, Security and Rescue Robotics {(SSRR)},
	year = {2013},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Linkoeping, Sweden},
	abstract = {Searching with a sensor for objects and to observe parts of a known environment efficiently is a fundamental problem in many real-world robotic applications such as household robots searching for objects, inspection robots searching for leaking pipelines, and rescue robots searching for survivors after a disaster. We consider the problem of identifying and planning efficient view point sequences for covering complex 3d environments. We compare empirically several variants of our algorithm that allow to trade-off schedule computation against execution time. Our results demonstrate that, despite the intractability of the overall problem, computing effective solutions for coverage search in real 3d environments is feasible.},
	keywords = {3D environments, coverage search, Educational institutions, execution time, household robots, image sequences, inspection robots, leaking pipelines search, objects search, path planning, Planning, rescue robots, Robot sensing systems, robot vision, robotic applications, schedule computation, Search problems, sensor, service robots, solid modelling, survivors search, Three-dimensional displays, Traveling salesman problems, view point sequences},
	doi = {10.1109/SSRR.2013.6719340},
	author = {Dornhege, C. and Kleiner, A. and Kolling, A.}
}
