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IEEE 17th International Conference on Automation Science and Engineering paper awards (with videos)

The IEEE International Conference on Automation Science and Engineering (CASE) is the flagship automation conference of the IEEE Robotics and Automation Society and constitutes the primary forum for cross-industry and multidisciplinary research in automation. Its goal is to provide a broad coverage and dissemination of foundational research in automation among researchers, academics, and practitioners. Here we bring you the online presentations by the finalists of the four awards given at the conference. Congratulations to all the finalists and winners!

Best student paper award

Winner

  • Designing a User-Centred and Data-Driven Controller for Pushrim-Activated Power-Assisted Wheels: A Case Study
    Mahsa Khalili, H.F. Machiel Van der Loos and Jaimie Borisoff

Finalists

  • Including Sparse Production Knowledge into Variational Autoencoders to Increase Anomaly Detection Reliability
    Tom Hammerbacher, Markus Lange-Hegermann, Gorden Platz

  • Synthesis and Implementation of Distributed Supervisory Controllers with Communication Delays
    Lars Moormann, Reinier Hendrik Jacob Schouten, Joanna Maria Van de Mortel-Fronczak, Wan Fokkink, Jacobus E. Rooda

  • Optimal Planning of Internet Data Centers Decarbonized by Hydrogen-Water-Based Energy Systems
    Jinhui Liu, Zhanbo Xu, Jiang Wu, kun liu, Xunhang Sun, Xiaohong Guan

  • Deep Reinforcement Learning for Prefab Assembly Planning in Robot-Based Prefabricated Construction
    Zhu Aiyu, Gangyan Xu, Pieter Pauwels, Bauke de Vries, Meng Fang

  • Singularity-Aware Motion Planning for Multi-Axis Additive Manufacturing
    Charlie C.L. Wang, Tianyu Zhang, Xiangjia Chen, Guoxin Fang, Yingjun Tian

Best conference paper award

Winner

  • Extended Fabrication-Aware Convolution Learning Framework for Predicting 3D Shape Deformation in Additive Manufacturing
    Yuanxiang Wang, Cesar Ruiz, Qiang Huang

Finalists

  • Probabilistic Movement Primitive Control Via Control Barrier Functions
    Mohammadreza Davoodi, Asif Iqbal, Joe Cloud, William Beksi, Nicholas Gans

  • Efficient Optimization-Based Falsification of Cyber-Physical Systems with Multiple Conjunctive Requirements
    Logan Mathesen, Giulia Pedrielli, Georgios Fainekos

Best application paper award

Winner

  • A Seamless Workflow for Design and Fabrication of Multimaterial Pneumatic Soft Actuators
    Lawrence Smith, Travis Hainsworth, Zachary Jordan, Xavier Bell, Robert MacCurdy

Finalists

  • Dynamic Multi-Goal Motion Planning with Range Constraints for Autonomous Underwater Vehicles Following Surface Vehicles
    James McMahon, Erion Plaku

  • OpenUAV Cloud Testbed: a Collaborative Design Studio for Field Robotics
    Harish Anand, Stephen A. Rees, Zhiang Chen, Ashwin Jose Poruthukaran, Sarah Bearman, Lakshmi Gana Prasad Antervedi, Jnaneshwar Das

Best healthcare automation paper award

Winner

  • Hospital Beds Planning and Admission Control Policies for COVID-19 Pandemic: A Hybrid Computer Simulation Approach
    Yiruo Lu, Yongpei Guan, Xiang Zhong, Jennifer Fishe, Thanh Hogan

Finalists

  • Rollout-Based Gantry Call-Back Control for Proton Therapy Systems
    Feifan Wang, Yu-Li Huang, Feng Ju

  • Progress in Development of an Automated Mosquito Salivary Gland Extractor: A Step Forward to Malaria Vaccine Mass Production
    Wanze Li, Zhuoqun Zhang, Zhuohong He, Parth Vora, Alan Lai, Balazs Vagvolgyi, Simon Leonard, Anna Goodridge, Ioan Iulian Iordachita, Stephen L. Hoffman, Sumana Chakravarty, B Kim Lee Sim, Russell H. Taylor


tags:


Daniel Carrillo-Zapata was awared his PhD in swarm robotics at the Bristol Robotics Lab in 2020. He now fosters the culture of "scientific agitation" to engage in two-way conversations between researchers and society.
Daniel Carrillo-Zapata was awared his PhD in swarm robotics at the Bristol Robotics Lab in 2020. He now fosters the culture of "scientific agitation" to engage in two-way conversations between researchers and society.

IEEE Robotics and Automation Society (RAS) strives to advance innovation, education, and fundamental and applied research in robotics and automation
IEEE Robotics and Automation Society (RAS) strives to advance innovation, education, and fundamental and applied research in robotics and automation





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