External Control
External control research focuses on developing methods to precisely manipulate and regulate the behavior of complex systems, ranging from robots and large language models to physical processes and biological systems. Current research emphasizes the development of robust and efficient control algorithms, often leveraging deep reinforcement learning, model predictive control, and generative models, alongside novel architectures like hybrid systems and multi-agent approaches. These advancements are crucial for improving the performance, safety, and adaptability of autonomous systems across diverse applications, from robotics and manufacturing to healthcare and environmental monitoring. The development of more efficient and generalizable control methods remains a key focus.
Papers
Control of Humanoid Robots with Parallel Mechanisms using Kinematic Actuation Models
Victor Lutz (LAAS-GEPETTO), Ludovic de Matteïs (LAAS-GEPETTO, WILLOW), Virgile Batto (LAAS-GEPETTO, AUCTUS)+2Université de Toulouse●Paris●centre de l’université de Bordeaux●Artificial and Natural Intelligence Toulouse InstituteBimanual Regrasp Planning and Control for Eliminating Object Pose Uncertainty
Ryuta Nagahama, Weiwei Wan, Zhengtao Hu, Kensuke HaradaOsaka University●Shanghai University
Flying Vines: Design, Modeling, and Control of a Soft Aerial Robotic Arm
Rianna Jitosho, Crystal E. Winston, Shengan Yang, Jinxin Li, Maxwell Ahlquist, Nicholas John Woehrle, C. Karen Liu, Allison M. OkamuraStanford UniversityDR-PETS: Learning-Based Control With Planning in Adversarial Environments
Hozefa Jesawada, Antonio Acernese, Giovanni Russo, Carmen Del VecchiobUniversity of Salerno●University of Sannio
Control, Optimal Transport and Neural Differential Equations in Supervised Learning
Minh-Nhat Phung, Minh-Binh TranDiffusion-Based Forecasting for Uncertainty-Aware Model Predictive Control
Stelios Zarifis, Ioannis Kordonis, Petros MaragosAthena Research Center●National Technical University of AthensModeling, Embedded Control and Design of Soft Robots using a Learned Condensed FEM Model
Etienne Ménager (WILLOW, DI-ENS), Tanguy Navez (DEFROST), Paul Chaillou (DEFROST, CRIStAL), Olivier Goury (INSERM, DEFROST)+4UMR 9189 CRIStAL●PSL Research UniversityLearning with Expert Abstractions for Efficient Multi-Task Continuous Control
Jeff Jewett, Sandhya SaisubramanianOregon State University
Task-Oriented Co-Design of Communication, Computing, and Control for Edge-Enabled Industrial Cyber-Physical Systems
Yufeng Diao, Yichi Zhang, Daniele De Martini, Philip Guodong Zhao, Emma Liying LiUniversity of Glasgow●University of Manchester●University of OxfordAcceptance or Rejection of Lots while Minimizing and Controlling Type I and Type II Errors
Edson Luiz Ursini, Elaine Cristina Catapani Poletti, Loreno Menezes da Silveira, José Roberto Emiliano Leite