Exploration and Coverage: A Deep Reinforcement Learning Approach

This work addresses the problem of exploration and coverage using visual inputs. Exploration and coverage is a fundamental problem in mobile robotics, the goal of which is to explore an unknown environment in order to gain vital information. Some of the diverse scenarios and applications in which exploratory robots can have a significant impact...

The Landing of a Quadcopter on Inclined Surfaces using Reinforcement Learning

Deep Reinforcement Learning (DRL) enables us to design controllers for complex tasks with a deep learning approach. It allows us to design controllers that are otherwise cumbersome to design with conventional control methodologies. Often, an objective for RL is binary in nature. However, exploring in environments with sparse rewards is a problem...

Online Reinforcement Learning Control of an Electromagnetic Manipulator

Machine Learning Control is a control paradigm that applies Artificial Intelligence methods to control problems. Within this domain, the field of Reinforcement Learning (RL) is particularly promising, since it provides a framework in which a control policy does not have to be programmed explicitly, but can be learned by an intelligent controller...

Adaptation of a non-linear controller based on Reinforcement Learning

Closed-loop control systems, which utilize output signals for feedback to generate control inputs, can achieve high performance. However, robustness of feedback control loops can be lost if system changes and uncertainties are too large. Adaptive control combines the traditional feedback structure with providing adaptation mechanisms that adjust...

Vision-based stabilization of micro quadrotors

On-board stabilization of quadrotors is often done using an Inertial Measurement Unit (IMU), aided by additional sensors to combat the IMU drift. For example, GPS readings can aid when flying outdoors, or when flying in GPS denied environments, such as indoors, visual information from one or more camera modules can be used. <br/>A single...