Reinforcement learning in domains with sparse rewards is a difficult problem, and a large part of the training process is often spent searching the state space in a more or less random fashion for learning signals. For ...

A good and reliable collision avoidance method is essential when operating Autonomous Surface Vehicles (ASVs) at sea. But even though avoiding collisions is the most important part, making sure the ASV's evasive maneuvers ...

Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pilots, thereby restricting the conditions UAVs can operate in and the types ...

This thesis is motivated by the increasing use of robots within numerous fields and in a vast range of applications. The use of robots provides several advantages, e.g. reduced labor costs, increased production and ...

This paper proposes a novel method for kinematic singularity avoidance for robot manipulators. Using set-based singularity avoidance tasks within the singularity-robust multiple task priority framework, avoidance of kinematic ...

Recurrent Neural Networks (RNNs) have a form of memory where the output from a node at one timestep is fed back as input the next timestep in addition to data from the previous layer. This makes them highly suitable for ...

The use of marine vessels, especially underwater vehicles, is rapidly increasing. Autonomous marine vehicles are a huge focus area within the oil and gas industry, and can also be utilized for scientific, environmental and ...

Additive manufacturing (AM) is a term that covers a variety of techniques for building custom-made, three dimensional structures. Such methods have moved from initially being used for creating simpli_ed models to enable ...

A robotic system can consist of a single or multiple agents with a fixed or mobile base, with full or under-actuation, and possibly redundancy. Collision avoidance is a crucial task for any robotic system and is necessary ...