V
主页
京东 11.11 红包
Understanding the Utility of Haptic Feedback in Telerobotic Devices by J Brown
发布人
Understanding the Utility of Haptic Feedback in Telerobotic Devices by Jeremy Brown, November 4, 2022 Abstract: The human body is capable of dexterous manipulation in many different environments. Some environments, however, are challenging to access because of distance, scale, and limitations of the body itself. In many of these situations, access can be effectively restored via a telerobot. Dexterous manipulation through a telerobot is possible only if the telerobot can accurately relay any sensory feedback resulting from its interactions in the environment to the operator. In this talk, I will discuss recent work from our lab focused on the application of haptic feedback in various telerobotic applications. I will begin by describing findings from recent investigations comparing different haptic feedback and autonomous control approaches for upper-extremity prosthetic limbs, as well as the cognitive load of haptic feedback in these prosthetic devices. I will then discuss recent discoveries on the potential benefits of haptic feedback in robotic minimally invasive surgery (RAMIS) training. Finally, I will discuss current efforts in our lab to measure haptic perception through novel telerobotic interfaces. Bio: Jeremy D. Brown is the John C. Malone Assistant Professor in the Department of Mechanical Engineering at Johns Hopkins University where he directs the Haptics and Medical Robotics (HAMR) Laboratory. He is also a member of the Laboratory for Computational Sensing and Robotics (LCSR) and the Malone Center for Engineering in Healthcare. Prior to joining Hopkins, Jeremy was a Postdoctoral Research Fellow at the University of Pennsylvania in the Haptics Research Group, which is part of Penn’s General Robotics, Automation, Sensing, and Perception (GRASP) Laboratory....
打开封面
下载高清视频
观看高清视频
视频下载器
What Makes Learning to Control Easy or Hard?by Nikolai Matni
New Complexities in New Aviation: UTM, UAM, and RAM by Raja Sengupta
Enabling a Responsive Grid with Distributed Load Control and Optimization
Easy, Hard or Convex?: The Role of Sparsity and Structure in Control Oriented ML
How Do We Learn to Use Learning in Manufacturing Systems by Kira Barton
Learning-based Koopman Modeling for Efficient State Estimation and Control ...
The Role of Adaptation in Learning, Safety, and Optimality by Anuradha Annaswamy
Frontiers of Autonomous Space Systems by Giusy Falcone
Are CMDPs Fundamentally Harder than MDPs? by Lei Ying
Driving the Elephant through the Landscape of Deep Networks Stefano Soatto
Walking the Boundary of Learning and Interaction by Dorsa Sadigh
Self-Powered Linear Feedback Control_ Necessary and Sufficient Conditions
Optimizing Intended Cost Functions by Anca Dragan
A Unifying, Data-Driven View of Locomotion by Shai Revzen
Embedded Convex Optimization for Control by Stephen Boyd
Pontryagin Meets Bellman by Alessandro Astolfi
Progress in Symmetry Preserving Robot Control by Maani Ghaffari
Towards Safe & Resilient Autonomy using Synergistic Control, Observation and ...
Safe Learning in Robotics by Claire Tomlin
Cheating with Neural Networks by Zico Kolter
Historical Survey and Emerging Challenges of Manufacturing Automation Modeling..
Physics-Guided Data-Driven Modeling for Control in Additive Manufacturing
Enabling Automatic Building Envelope Retrofits Using Controls & Machine Learning
Equitable Dynamic Systems Engineering by Hugo Gonzalez Villasanti
Real-time Distributed Decision Making in Networked Systems by Na Li
Why Would One Want a Multi-agent System Unstable by Mrdjan Jankovic
Planning and Discussion Session
Influencing Interactive Mixed-Autonomy Systems by Dorsa Sadigh
Safe and Efficient Exploration in Reinforcement Learning by Andreas Krause
Control Barrier Functions & Neural Networks for Handling Risk and Uncertainty...
Competence-aware Planning and Control by Hamidreza Modares
Formal Learning and Control of Large-Scale Cyber-Physical Systems via ISS ...
Feedback in Wafer Scanners: Use the Unstable by Marcel Heertjes @ CCTA 2021
Coordinated Control of Multi-agent Systems: Lessons From Collective Animal ...
A Dynamic Obfuscation Framework for Privacy and Utility by Stephane Lafortune
Dissipation-based Controller Synthesis: Successes and Challenges by C Scherer
Safe, Interaction-Aware Decision Making and Control for Robot Autonomy by Pavone
Bridging the Gap Between Planning and Control: A Cascaded MPC Approach by J Z Lu
Modeling and Control Of Digital Printing and Imaging Systems by George Chiu
Learning Manipulation — and Why I (Still) Like "F=ma" by Russ Tedrake