@conference{Li2024ActiveSurface,

title = {Active Surface with Passive Omni-Directional Adaptation for In-Hand Manipulation},

author = {Sen Li and Fang Wan and Chaoyang Song},

url = {https://iftomm-world.org/conferences/remar2024/#:~:text=Following%20successful%20completion%20in%20London%20(2009),%20Tianjin%20(2012),%20Beijing},

doi = {10.1109/ReMAR61031.2024.10619925},

year  = {2024},

date = {2024-06-23},

urldate = {2024-06-23},

booktitle = {IEEE/IFToMM International Conference on Reconfigurable Mechanisms and Robots (ReMAR2024)},

address = {Chicago, USA},

abstract = {Soft fingers with omni-directional adaptability ex- cel in 3D twisting, outperforming two-dimensional self-adaptive hands using a finger rotation mechanism to achieve similar adaptability. In this study, we present the design of a soft robotic finger with an active surface on an omni-adaptive structure, which can be easily installed on existing grippers and achieve stability and dexterity for in-hand manipulation. The system’s active surfaces initially transfer the object from the fingertip segment with less compliance to the middle segment of the finger with superior adaptability. Despite the omni-directional deformation of the finger, in-hand manipulation can still be executed with controlled active surfaces. We characterized the soft finger’s stiffness distribution and simplified models to assess the feasibility of lifting and reorienting a grasped object in a 3D twisting state. A set of experiments on in-hand manipulation was performed with the proposed fingers, demonstrating the dexterity and robustness of the strategy.},

keywords = {Authorship - Corresponding, Conf - ReMAR},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chen2024EvolutionaryMorphology,

title = {Evolutionary Morphology Towards Overconstrained Locomotion via Large-Scale, Multi-Terrain Deep Reinforcement Learning},

author = {Yenan Chen and Chuye Zhang and Pengxi Gu and Jianuo Qiu and Jiayi Yin and Nuofan Qiu and Guojing Huang and Bangchao Huang and Zishang Zhang and Hui Deng and Wei Zhang and Fang Wan and Chaoyang Song},

url = {https://iftomm-world.org/conferences/remar2024/#:~:text=Following%20successful%20completion%20in%20London%20(2009),%20Tianjin%20(2012),%20Beijing},

doi = {10.1109/ReMAR61031.2024.10618090},

year  = {2024},

date = {2024-06-23},

urldate = {2024-06-23},

booktitle = {IEEE/IFToMM International Conference on Reconfigurable Mechanisms and Robots (ReMAR2024)},

address = {Chicago, USA},

abstract = {While the animals' Fin-to-Limb evolution has been well-researched in biology, such morphological trans- formation remains under-adopted in the modern design of advanced robotic limbs. This paper investigates a novel class of overconstrained locomotion from a design and learning perspective inspired by evolutionary morphology, aiming to integrate the concept of 'intelligent design under constraints' - hereafter referred to as constraint-driven design intelligence - in developing modern robotic limbs with superior energy efficiency. We propose a 3D-printable design of robotic limbs parametrically reconfigurable as a classical planar 4-bar linkage, an overconstrained Bennett linkage, and a spherical 4-bar linkage. These limbs adopt a co-axial actuation, identical to the modern legged robot platforms, with the added capability of upgrading into a wheel-legged system. Then, we implemented a large-scale, multi-terrain deep reinforcement learning framework to train these reconfigurable limbs for a comparative analysis of overconstrained locomotion in energy efficiency. Results show that the overconstrained limbs exhibit more efficient locomotion than planar limbs during forward and sideways walking over different terrains, including floors, slopes, and stairs, with or without random noises, by saving at least 22% mechanical energy in completing the traverse task, with the spherical limbs being the least efficient. It also achieves the highest average speed of 0.85m/s on flat terrain, which is 20% faster than the planar limbs. This study paves the path for an exciting direction for future research in overconstrained robotics leveraging evolutionary morphology and reconfigurable mechanism intelligence when combined with state-of-the-art methods in deep reinforcement learning.},

keywords = {Authorship - Corresponding, Conf - ReMAR},

pubstate = {published},

tppubtype = {conference}

}

@conference{Song2012ASpecial,

title = {A Special Wohlharts Double-Goldberg 6R Linkage and Its Multiple Operation Forms among 4R and 6R Linkages},

author = {Chaoyang Song and Yan Chen},

doi = {10.1007/978-1-4471-4141-9_5},

year  = {2012},

date = {2012-07-09},

urldate = {2012-07-09},

booktitle = {ASME/IEEE International Conference on Reconfigurable Mechanisms and Robots (ReMAR2012)},

address = {Tianjin, China},

keywords = {Authorship - First Author, Award - Travel Grant, Award - Young Delegate Travel Grant, Conf - ReMAR},

pubstate = {published},

tppubtype = {conference}

}