Category: Uncategorized
Decision Making under Uncertainty
Robotics Seminar Series. Twelfth Session – 4th December 2020. Speaker: Joni Pajarinen
Autonomous Overtaking Maneuver Under Complex Driving Conditions
Robotics Seminar Series.Eleventh Session, Talk 2 – 6th November 2020. Speaker: Jiyo Palatti
Probabilistic Surface Friction Estimation Based on Visual and Haptic Measurements
Robotics Seminar Series.Eleventh Session, Talk 1 – 6th November 2020. Speaker: Tran Nguyen Le
Video on “Probabilistic Surface Friction Estimation Based on Visual and Haptic Measurements”
Watch the video demonstration of our latest paper on friction coefficient estimation
Master thesis on “Evaluating Domain Randomization”
Data collection is a major obstacle to applying deep learning methods to robotics. In this thesis, we propose to perform a quantitative study of the use of synthetic data from 3D software and physics simulators to train machine learning models that can later be deployed on physical systems.
Safe Model Predictive Control
Safe Model Predictive Control (Safe MPC) aims to ensure that a physical system’s safety constraints are satisfied with high probability. Our research is on extending constrained MPC methods to cope with probabilistic safety constraints. We further research modeling uncertainty of dynamics to ensure safe exploration when combined with safety constraints learned in simulation, and learning powerful data-efficient surrogate models for complex dynamics.
Assignment on “Differential Dynamic Programming with Safety Constraints”
The goal of this assignment is to understand the constrained DDP with safety precautions and implement it on a real robot, e.g., Turtlebot 3 Waffle Pi. It is expected to perform the experiments in an engineered environment in which the positions of the robot and the obstacles will be measured by an external vision based system (motion capture system).