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Article
Open AccessDeep Model-Based Reinforcement Learning for Predictive Control of Robotic Systems with Dense and Sparse Rewards
Sparse rewards and sample efficiency are open areas of research in the field of reinforcement learning. These problems are especially important when considering applications of reinforcement learning to roboti...
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Article
Design of a Decentralized Strategy for Layered Self-Assembly of 3D Structures Using Robotic Blocks
In self-assembly tasks, local interactions between robotic structure parts induce a collective behaviour that guides the robots to assume a desired shape. In this work, we propose a self-assembly strategy for ...
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Article
Multiple Model Distributed EKF for Teams of Target Tracking UAVs using T Test Selection
Target tracking and estimation using teams of unmanned aerial vehicles is essential to achieving autonomous drone systems. However, one problem that degrades target estimation is the limitation of the chosen m...
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Article
Correction to: Improving Control Performance of Unmanned Aerial Vehicles through Shared Experience
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Article
Improving Control Performance of Unmanned Aerial Vehicles through Shared Experience
This work proposes a novel approach for improving the control performance of Unmanned Aerial Vehicles (UAVs) through cooperative reinforcement learning. By sharing their experience, it is shown that multiple U...
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Article
Iterative Decentralized Planning for Collective Construction Tasks with Quadrotors
This paper describes an iterative decentralized planning and learning method, based on stochastic learning automata theory and heuristic search techniques, to generate construction and motion strategies to bui...
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Article
A Learning Invader for the “Guarding a Territory” Game
This paper explores the use of a learning algorithm in the “guarding a territory” game. The game occurs in continuous time, where a single learning invader tries to get as close as possible to a territory befo...
