Author: arndtk1
ICRA 2023, here we come!
The Intelligent Robotics group will attend to ICRA 2023. Read more!
Meta-learning — Introduction and overview
Robotics Seminar Series. Fifth Session – 22nd May 2020. Speaker: Karol Arndt
Sim-to-real transfer in reinforcement learning
Getting robots to autonomously learn to perform various tasks is often a long-term process, during which the robot’s exploratory actions can be unpredictable and potentially dangerous to the surrounding environment and to the robot itself. To mitigate the risk of hardware damage and to speed up the learning process, initial phases of learning are often […]
Robot Learning
Programming robots to perform various tasks often requires extensive domain knowledge and a tedious programming process. The size of the program rapidly grows with task complexity; explicitly programming a robot to perform challenging tasks in a variety of environments would require the programmer to write routines for an enormous number of situations that may possibly […]
Robot Control
Robotic tasks in real-world applications generally involve uncertain, stochastic and dynamic environments. Pre-programming based solutions either do not work or give unsatisfactory results in such environments. This requires to generate cautious control strategies that provide optimum actions to perform the desired task while considering the effects of the uncertainties in the environment. Robot control aims […]