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Description:
In this edition of QuEST, Dr. Raj Sharma and Jasper Craig with the SAFE Autonomy Team in ACT3 will discuss their work on implementation of reinforcement learning (RL) in a simulated environment.
Key Moments in the video include:
Quadrotor Dynamics
Differential flatness
Linear Quadratic Controller (LQR)
Formation Consensus
Reinforcement Learning (RL) for Trajectory Control
Benefits of LQR and RL
Future Work
Audience questions:
Kinematics that you used for this control - does that change for battery-powered or certainly gas-powered weight of the craft changes? How do people model that, or is it necessary to model that?
Would there be a place in that matrix you were describing a moment ago to account for some of those things?
Does every agent or node have perfect knowledge of the leader?
What mechanisms were used to work with Kerianne’s group - Summer Faculty Fellowship?
| Date Taken: | 09.15.2023 |
| Date Posted: | 11.07.2024 14:55 |
| Category: | Video Productions |
| Video ID: | 943098 |
| VIRIN: | 230915-F-BA826-8948 |
| Filename: | DOD_110672768 |
| Length: | 00:55:05 |
| Location: | US |
| Downloads: | 2 |
| High-Res. Downloads: | 2 |
This work, Dr. Raj Sharma and Jasper Craig, by Kevin D Schmidt, identified by DVIDS, must comply with the restrictions shown on https://www.dvidshub.net/about/copyright.
