@conference{Liu2023JigsawBased,

title = {Jigsaw-based Benchmarking for Learning Robotic Manipulation},

author = {Xiaobo Liu and Fang Wan and Sheng Ge and Haokun Wang and Haoran Sun and Chaoyang Song},

url = {http://www.ieee-arm.org/icarm2023/},

doi = {10.1109/ICARM58088.2023.10218784},

year  = {2023},

date = {2023-07-08},

urldate = {2023-07-08},

booktitle = {IEEE International Conference on Advanced Robotics and Mechatronics (ICARM2023)},

address = {Sanya, China},

abstract = {Benchmarking provides experimental evidence of the scientific baseline to enhance the progression of fundamental research, which is also applicable to robotics. In this paper, we propose a method to benchmark metrics of robotic manipulation, which addresses the spatial-temporal reasoning skills for robot learning with the jigsaw game. In particular, our approach exploits a simple set of jigsaw pieces by designing a structured protocol, which can be highly customizable according to a wide range of task specifications. Researchers can selectively adopt the proposed protocol to benchmark their research outputs, on a comparable scale in the functional, task, and system-level of details. The purpose is to provide a potential look-up table for learning-based robot manipulation, commonly available in other engineering disciplines, to facilitate the adoption of robotics through calculated, empirical, and systematic experimental evidence.},

keywords = {Authorship - Corresponding, Award - Best Conference Paper Finalist, Award - Paper, Conf - ICARM},

pubstate = {published},

tppubtype = {conference}

}

@conference{Guo2023UnderwaterIntention,

title = {Underwater Intention Recognition using Head Motion and Throat Vibration for Supernumerary Robotic Assistance},

author = {Yuqin Guo and Rongzheng Zhang and Wanghongjie Qiu and Harry Asada and Fang Wan and Chaoyang Song},

url = {https://case2023.org/},

doi = {10.1109/CASE56687.2023.10260480},

year  = {2023},

date = {2023-06-26},

urldate = {2023-06-26},

booktitle = {IEEE International Conference on Automation Science and Engineering (CASE2023)},

address = {Auckland, New Zealand},

abstract = {This study presents a multi-modal mechanism for recognizing human intentions while diving underwater, aiming to achieve natural human-robot interactions through an underwater superlimb for diving assistance. The underwater environment severely limits the divers' capabilities in intention expression, which becomes more challenging when they intend to operate tools while keeping control of body postures in 3D with the various diving suits and gears. The current literature is limited in underwater intention recognition, impeding the development of intelligent wearable systems for human-robot interactions underwater. Here, we present a novel solution to simultaneously detect head motion and throat vibrations under the water in a compact, wearable design. Experiment results show that using machine learning algorithms, we achieved high performance in integrating these two modalities to translate human intentions to robot control commands for an underwater superlimb system. This study's results paved the way for future development in underwater intention recognition and underwater human-robot interactions with supernumerary support.},

keywords = {Authorship - Corresponding, Award - Best Healthcare Automation Paper, Award - Paper, Conf - CASE},

pubstate = {published},

tppubtype = {conference}

}

@conference{Yi2016ASoft,

title = {A Soft Robotic Glove for Hand Motion Assistance},

author = {Juan Yi and Zhong Shen and Chaoyang Song and Zheng Wang},

doi = {10.1109/rcar.2016.7784010},

year  = {2016},

date = {2016-06-06},

urldate = {2016-06-06},

booktitle = {IEEE International Conference on Real-time Computing and Robotics (RCAR2016)},

address = {Angkor Wat, Cambodia},

keywords = {Authorship - Co-Author, Award - Best Conference Paper Finalist, Award - Paper, Conf - RCAR},

pubstate = {published},

tppubtype = {conference}

}

@conference{Song2015RiskAnd,

title = {Risk and Innovation Balance in Crowdfunding New Products},

author = {Chaoyang Song and Jianxi Luo and Katja Hölttä-Otto and Kevin Otto and Warren Seering},

url = {https://www.designsociety.org/publication/37919/risk+and+innovation+balance+in+crowdfunding+new+products},

year  = {2015},

date = {2015-07-27},

urldate = {2015-07-27},

booktitle = {International Conference on Engineering Design (ICED2015)},

address = {Milan, Italy},

abstract = {Many have considered that innovation through new and small companies is a vital driver for sustainable economic growth. Recent growth in Web 2.0 demands small companies to further incorporate risk management while developing innovative products. How to balance risk and innovation during new product development becomes a priority for small companies to survive the competition. Yet, the approach is not likely similar to that employed by incumbent firms. This paper explores innovation versus risk for small companies using crowdfunding products as a proxy for analysis. A database with 127 consumer electronics, namely 3D printers and smart watches, are collected from Kickstarter and Indiegogo. The metric of Real-Win-Worth is adapted to provide a well-rounded assessment of the product’s innovation, risk and other related business and engineering aspects. Our result suggests a preliminary framework of innovation and risk balance for crowdfunding NPD success. A statistical model is developed to correlate the amount of crowdfunding raised with 64% predictability. These results may contribute to better understand and balance risk and innovation in crowdfunding and small company contexts.},

keywords = {Authorship - First Author, Award - Paper, Award - Reviewers' Favorites Award, Conf - ICED},

pubstate = {published},

tppubtype = {conference}

}