V
主页
京东 11.11 红包
Safe Learning in Robotics by Claire Tomlin
发布人
Safe Learning in Robotics by Claire Tomlin (UC Berkeley) @ Learning for Dynamics and Control, MIT May 31, 2019
打开封面
下载高清视频
观看高清视频
视频下载器
Safe Learning in Robotics by Claire Tomlin
Learning-based Planning and Control: Opportunities and Challenges by J. How
Learning Manipulation — and Why I (Still) Like "F=ma" by Russ Tedrake
Safe Exploration in Reinforcement Learning by Andreas Krause (ETH Zuerich)
Safe and Efficient Exploration in Reinforcement Learning by Andreas Krause
Safe Autonomy with Deep Learning in the Feedback Loop by George J. Pappas
Infusing Physics and Structure into Machine Learning by Anima Anandkumar
Safe, Interaction-Aware Decision Making and Control for Robot Autonomy by Pavone
Dynamics and Control of Differential Learning by Stefano Soatto (UC Berkeley)
Set-Based Methods for Hierarchical Model Predictive Control & Beyond by J Koeln
The Shades of Reinforcement Learning by John Tsitsiklis
Learning Certifiably Safe Control for Large-scale Autonomous Systems by C Fan
Planning and Discussion Session
Formal Learning and Control of Large-Scale Cyber-Physical Systems via ISS ...
Doing Robotics in Digital Labs: Or How Simulations Fuel Robotics Development
Machine Learning: Bane Or Boon For Control? by Miroslav Krstic @CDC2023
Bionic Learning Network – Inspired by Nature by Heinrich Frontzek @IFAC2014
Learning and Control for Safety, Efficiency, and Resiliency of Embodied AI
How Do We Learn to Use Learning in Manufacturing Systems by Kira Barton
A Data-Driven Approach To Nonlinear Systems Control, Robotics, and Life Sciences
Control Has Met Learning: Aspirational Lessons from Adaptive Control Theory
IFAC Industry Connect: Making the Leap from Academia to Entrepreneurship
Advances and Opportunities of AI and Machine Learning In Industrial Process M...
Distributed Machine Learning over Networks by Francis Bach @CDC2019
Navigation Robot for the Visually Impaired by Chieko Asakawa @ IROS2022
Mathematics of Deep Learning by René Vidal @ ACC2019
Leveraging Learning & Opt.-based Planning for Multi-Robot Systems by P. Tokekar
New Complexities in New Aviation: UTM, UAM, and RAM by Raja Sengupta
Understanding the Utility of Haptic Feedback in Telerobotic Devices by J Brown
Fast and Flexible Multi-Agent Decision-Making by Naomi Leonard @ CDC 2023
Enabling a Responsive Grid with Distributed Load Control and Optimization
The Role of Adaptation in Learning, Safety, and Optimality by Anuradha Annaswamy
Toward Human Assistive Robotics for Aiding Human Activity by Mihoko Niitsuma
The Impact of Model-Based Design on Controls: Today & in the Future by J Little
Dual Control Revisited by Anders Rantzer @ CDC 2024
Inverse Optimal Safe Control by Miroslav Krstic
Data-Enabled Predictive Control by Florian Dörfler
Robot and Remote-controlled Machine Technology for Accident Response and ...
Why Would We Want a Multi-agent System Unstable? by Mrdjan Jankovic @ACC2023
Control Design Based on Deep Learning by Draguna Vrabie