Abstract:
Soft Robotics recently has drawn significant interest in diverse applications, due to the rich shapes and motions possible compared to more traditional rigid robotics. We aimed to develop a platform technology and accompanying design principles for highly-actuated soft robotic sheets. For physical construction, we focus on Large-Area Electronics (LAE), which enables flexible formfactor and scalability of integrated sensing and actuation devices. LAE, currently widely deployed commercially for flat-panel displays, thus has the potential to open up rich opportunities for advanced soft robotics. However, it also presents two major challenges: (1) modeling the mechanical dynamics of the rich motions possible with soft materials; and (2) harnessing the many integrated devices through algorithms for high-dimensional control.
Well-generalizing and robust models are necessary for robot design and control, yet soft materials lead to significant dependencies on external and internal/interacting forces. We developed an analytical model of the robot that captures the full soft body deformation. We use this to design an inchworm-like crawling robot. The model and the design have been validated with both robot-scale simulations and physical experiments. Ongoing research moves to further experimental validation, integration of on-board sensors, and design of higher-level control algorithms.
Zhiwu Zheng Bio:
Zhiwu Zheng received the B.S. degree in physics from Nanjing University, Nanjing, China, in 2016, and the M.A. degree in electrical engineering from Princeton University, Princeton, NJ, USA, in 2019. He is currently working toward the Ph.D. degree in electrical engineering at Princeton University.
During his undergraduate study, he worked on nanoelectronic, photonic and quantum devices for next-generation electrically controlled photonic computation systems. He was an exchange student working on 2D-material electronic devices at National University of Singapore, Singapore, during the spring semester of 2015. His current research interests and expertise focus on machine learning and statistical signal processing algorithms, architectures, circuits and devices for advanced sensing systems and robotics.
Mr. Zheng was the recipient of 2018-2019 and 2019-2020 Fellowships of the Program in Plasma Science and Technology (PPST) at Princeton University, 2014 Shi Shi-Yuan Scholarship and 2014 Infineon Scholarship, as well as 2013-2016 Fellowship of China National Innovational Undergraduates Program, Nanjing University 2013 Excellent Student, 2013 Scientific Innovation Scholarship, and 2013-2014, 2014-2015, 2015-2016 First-Place Talent Scholar Awards. He is currently serving as peer reviewers for IEEE Transactions on Biomedical Circuits and Systems as well as International Journal of Biomedical Science and Engineering.
Prakhar Kumar Bio:
Prakhar Kumar received his B.E.(Hons) in Electrical and Electronics Engineering from BITS Pilani, Pilani Campus, India in 2016. His current research focuses on developing hybrid sensing systems by bringing together Large Area Electronics (LAE) and CMOS VLSI technologies. More specifically, he is interested in designing technology platforms that can enable machine learning algorithms to carry out inference and state estimation tasks effectively.
