Gaussian Process-based Visual Pursuit Control with Automatic Gain Tuning
Author:
Affiliation:
1. The University of Tokyo,Department of Information Physics and Computing,Tokyo,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9965973/9965785/09966033.pdf?arnumber=9966033
Reference19 articles.
1. Online Learning-Based Trajectory Tracking for Underactuated Vehicles With Uncertain Dynamics
2. Learning Self-Triggered Controllers With Gaussian Processes
3. Provably Robust Learning-Based Approach for High-Accuracy Tracking Control of Lagrangian Systems
4. Visual Pursuit Control with Target Motion Learning via Gaussian Process
5. Real-time, low-latency closed-loop feedback using markerless posture tracking
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1. A Control Barrier Function Approach for Observer-based Visually Safe Pursuit Control with Spherical Obstacles*;IFAC-PapersOnLine;2023
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