Robotics

Our work “Learning to detect slip through tactile estimation of the contact force field and its entropy properties” (Xiaohai Hu, Aparajit Venkatesh, Yusen Wan, Guiliang Zheng, Neel Anand Jawale, Navneet Kaur, Xu Chen, and Paul Birkmeyer), presented at MECC 2024, won the best Robotic Paper award from the ASME Dynamic Systems and Control Division. Read the extended journal version of the paper at Elsevier Mechatronics. Huge thanks to Xiaohai(Bob) Hu, who tirelessly iterated through several revisions, and all the other co-authors, for their contributions. A big thank you to Amazon Science for their generous funding that supported this work.

Oct 25, 2024

I am honored to have been named an ARM Champion, an award recognizing individuals from over ARM’s 400 member organizations who go above and beyond the standard call of membership. This recognition is especially meaningful as I was nominated by both the internal ARM Institute technology team and Debbie Franklin, Associate Vice President of Strategic Initiatives and Industry Engagement at Wichita State University. I am deeply grateful for the support and encouragement of my colleagues and collaborators who make achievements like this possible. You can read more about the 2024 Class of Champions here. Thank you all for being an integral part of this journey!

Sep 20, 2024

“Agile Surface Inspection Framework for Aerospace Components Using Unsupervised Machine Learning,” Arun Nandagopal, Abhishek Kulkarni, Colin Acton, Krithika Manohar, and Xu Chen, Japan Institute of Systems, Control, and Information Engineers (ISCIE) / ASME International Symposium on Flexible Automation It’s been almost six years since we started working on robotic high-precision inspection. There have been so many exciting results (and unexpected happy surprises) along the path. This segmentation result takes in complex geometries, performs optimization to assure full-surface coverage, and provides occlusion-free image capture. The processes are strategically designed to utilize the optimal number of imaging locations, make in-focus image acquisitions, and maintain their applicability across different robots.

Jul 24, 2024

Feb 20, 2024

Our project on “Adaptive Grasping and Object Manipulation using Visual and Tactile Feedback” was selected in the inaugural set of faculty research awards to advance AI and robotics. The UW + Amazon Science Hub was founded in February 2022 and housed in the University of Washington College of Engineering. The projects were selected through a joint review process between the UW Advisory Group and Amazon. Each recipient will each receive up to $100,000 in research funding from Amazon, and each year-long project will address a real-world, cutting-edge challenge in AI or robotics.

Aug 10, 2022

Robots that remedy burdensome and subjective human inspections.

Jul 22, 2020

Help build a national robotic resource map for manufacturing.

Jul 22, 2020

(as Guest Editor) Owing to the explosive advancements in recent years in the areas of computational intelligence, material synthesis, and device integration, a new era of intelligent robotics, featuring unprecedented capabilities of sensing, actuation, and decision making, has arrived. Various newly developed robotic systems have penetrated into virtually all industrial sectors, ranging from manufacturing, energy, aerospace and naval, infrastructure, to health care and service, etc. They possess remarkably enhanced performances in terms of accuracy, adaptivity, reliability, and autonomy, and are poised to change fundamentally our modalities of working and living. The new accomplishments exemplify the collaborative efforts by academia and industry that are currently accelerating. Aiming at documenting and disseminating the progresses and identifying growth opportunities, this focused section showcases a number of recent technological achievements in the learning and control of robotic systems. It includes nine papers that share the common theme of robotic systems utilizing complex or heterogeneous data in their design and control through advanced learning and estimation techniques.

Jul 22, 2020

Building robots that combine vision, AI, and manipulation to play games, perform tasks, and advance research.

Jul 22, 2020

My student Hui Xiao received this Best Student Paper on Robotics award on October 11, 2019, from the ASME Dynamic Systems and Control Division. Our paper, titled “Following fast-dynamic targets with only slow and delayed visual feedback - a Kalman filter and model-based prediction approach,” addresses key challenges in real-time vision-based robotic applications.

Oct 11, 2019