About Course
Robotics and Autonomous Systems
Robots must be able to accomplish tasks in a wide variety of scenarios to be effective in unconstrained environments – they must be able to generalize. For a variety of challenges, we’ve seen excellent outcomes from machine learning algorithms that generalize to large real-world datasets. As a result, machine learning gives robots a potent tool to accomplish the same.
Machine learning algorithms for robotics, on the other hand, frequently generalize narrowly inside a specific laboratory context. In this session, I’ll talk about the problems that robots confront in comparison to traditional machine learning problem settings, and how we might rethink both our robot learning algorithms and our data sources to enable robots to generalize broadly spans jobs, settings, and robot platforms
This course is intended for the following individuals:
Robotics enthusiasts, as well as anyone interested in learning more about robotic, are welcome to attend.
Course Content
Robotics and Autonomous Systems
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Seminar – Designing bioinspired aerial robots with feathered morphing wings
35:43 -
Seminar – Toward robust manipulation in complex environments
58:54 -
Seminar – Safe and Robust Perception-Based Control
56:27 -
Seminar – Safety-Critical Control of Dynamic Robots
00:00 -
Seminar – Designing More Effective Remote Presence Systems for Human Connection
00:00 -
Seminar – Robotic Autonomy and Perception in Challenging Environments
58:04 -
Seminar – Distributed Perception and Learning Between Robots and the Cloud
47:25 -
Seminar – The Next Generation of Robot Learning
00:00 -
Seminar – Hands in the Real World: Grasping Outside the Lab
00:00 -
Seminar – Model Predictive Control of Hybrid Dynamical Systems
00:00 -
Seminar – Learning and Predictions in Autonomous Systems
00:00 -
Seminar – Field-hardened Robotic Autonomy
00:00 -
Seminar – Self-Supervised Pseudo-Lidar Networks
01:05:17 -
Seminar – Modeling and Control for Robotic Assistants
00:00 -
Seminar – Bridging model-based and data-driven reasoning for safe human-centered robotics
00:00
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