62 citations · 148 across the 5 of their papers we have counts for
5 papers · 1 filter
Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization
Mikko Lauri, Joni Pajarinen, Jan Peters +1
3D scene models are useful in robotics for tasks such as path planning, object manipulation, and structural inspection. We consider the problem of creating a 3D model using depth i…
Learning to Play Table Tennis From Scratch using Muscular Robots
Dieter Büchler, Simon Guist, Roberto Calandra +3
Dynamic tasks like table tennis are relatively easy to learn for humans but pose significant challenges to robots. Such tasks require accurate control of fast movements and precise…
Orientation Attentive Robotic Grasp Synthesis with Augmented Grasp Map Representation
Georgia Chalvatzaki, Nikolaos Gkanatsios, Petros Maragos +1
Inherent morphological characteristics in objects may offer a wide range of plausible grasping orientations that obfuscates the visual learning of robotic grasping. Existing grasp…
Learning to Fly via Deep Model-Based Reinforcement Learning
Philip Becker-Ehmck, Maximilian Karl, Jan Peters +1
Learning to control robots without requiring engineered models has been a long-term goal, promising diverse and novel applications. Yet, reinforcement learning has only achieved li…
Deep Adversarial Reinforcement Learning for Object Disentangling
Melvin Laux, Oleg Arenz, Jan Peters +1
Deep learning in combination with improved training techniques and high computational power has led to recent advances in the field of reinforcement learning (RL) and to successful…