Print Email Facebook Twitter EasySRRobot Title EasySRRobot: An Easy-to-Build Self-Reconfigurable Robot with Optimized Design Author Yu, Minjing (Tsinghua University) Liu, Yong-Jin (Tsinghua University) Wang, C.C. (TU Delft Materials and Manufacturing) Date 2017 Abstract Self-reconfigurable modular robots (SRRobot) that can change their shape and function in different environments according to different tasks have caught a lot of attention recently. Most existing prototypes use professional electronic components with relatively expensive cost and high barrier of fabrication. In this paper, we present a low-cost SRRobot with double-cube modules. Our system is easy-to-build even for novices as all electric components are off-the-shelf and the structural components in plastics are made by 3D printing. To have a better design of interior structures, we first construct a design space for all feasible solutions that satisfy the constraints of fabrication. Then, an optimized solution is found by an objective function incorporating the factors of space utilization, structural sound-ness and assembly complexity. Thirty EasySRRobot modules are manufactured and assembled. The functionality of our algorithm is demonstrated by comparing an optimized interior design with other two feasible designs and realizing different motions on an EasySRRobot with four modules. Subject self-reconfigurationmodular robotoptimal design To reference this document use: http://resolver.tudelft.nl/uuid:e50f6817-8e95-49db-b6e9-590fa571e547 DOI https://doi.org/10.1109/ROBIO.2017.8324563 Publisher IEEE ISBN 978-1-5386-3743-2 Source 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Event IEEE-ROBIO 2017, 2017-12-05 → 2017-12-08, The Parisian Macao, Macau, China Bibliographical note Accepted author manuscript Part of collection Institutional Repository Document type conference paper Rights © 2017 Minjing Yu, Yong-Jin Liu, C.C. Wang Files PDF easysrrobot_low_cost.comp ... sed_1_.pdf 753.27 KB Close viewer /islandora/object/uuid:e50f6817-8e95-49db-b6e9-590fa571e547/datastream/OBJ/view