9 citations · 34 across the 14 of their papers we have counts for
17 papers
What Matters for Active Texture Recognition With Vision-Based Tactile Sensors
Alina Böhm, Tim Schneider, Boris Belousov +6
This paper explores active sensing strategies that employ vision-based tactile sensors for robotic perception and classification of fabric textures. We formalize the active samplin…
Pseudo-Likelihood Inference
Theo Gruner, Boris Belousov, Fabio Muratore +2
Simulation-Based Inference (SBI) is a common name for an emerging family of approaches that infer the model parameters when the likelihood is intractable. Existing SBI methods eith…
Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation
Yaonan Zhu, Shukrullo Nazirjonov, Bingheng Jiang +6
Vision-based tactile sensors have gained extensive attention in the robotics community. The sensors are highly expected to be capable of extracting contact information i.e. haptic…
How Crucial is Transformer in Decision Transformer?
Max Siebenborn, Boris Belousov, Junning Huang +1
Decision Transformer (DT) is a recently proposed architecture for Reinforcement Learning that frames the decision-making process as an auto-regressive sequence modeling problem and…
Active Exploration for Robotic Manipulation
Tim Schneider, Boris Belousov, Georgia Chalvatzaki +3
Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning in recent years. One of the key challenges in manipulation i…
Active Inference for Robotic Manipulation
Tim Schneider, Boris Belousov, Hany Abdulsamad +1
Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning in the last decades. One of the central challenges of manipu…
Continuous-Time Fitted Value Iteration for Robust Policies
Michael Lutter, Boris Belousov, Shie Mannor +3
Solving the Hamilton-Jacobi-Bellman equation is important in many domains including control, robotics and economics. Especially for continuous control, solving this differential eq…
Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative Entropy Trust-Regions
Hany Abdulsamad, Tim Dorau, Boris Belousov +2
Trajectory optimization and model predictive control are essential techniques underpinning advanced robotic applications, ranging from autonomous driving to full-body humanoid cont…
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning
Pascal Klink, Hany Abdulsamad, Boris Belousov +3
Across machine learning, the use of curricula has shown strong empirical potential to improve learning from data by avoiding local optima of training objectives. For reinforcement…
Underactuated Waypoint Trajectory Optimization for Light Painting Photography
Christian Eilers, Jonas Eschmann, Robin Menzenbach +3
Despite their abundance in robotics and nature, underactuated systems remain a challenge for control engineering. Trajectory optimization provides a generally applicable solution,…
HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints
Michael Lutter, Boris Belousov, Kim Listmann +2
Learning optimal feedback control laws capable of executing optimal trajectories is essential for many robotic applications. Such policies can be learned using reinforcement learni…
Receding Horizon Curiosity
Matthias Schultheis, Boris Belousov, Hany Abdulsamad +1
Sample-efficient exploration is crucial not only for discovering rewarding experiences but also for adapting to environment changes in a task-agnostic fashion. A principled treatme…
Self-Paced Contextual Reinforcement Learning
Pascal Klink, Hany Abdulsamad, Boris Belousov +1
Generalization and adaptation of learned skills to novel situations is a core requirement for intelligent autonomous robots. Although contextual reinforcement learning provides a p…
Building a Library of Tactile Skills Based on FingerVision
Boris Belousov, Alymbek Sadybakasov, Bastian Wibranek +3
Camera-based tactile sensors are emerging as a promising inexpensive solution for tactile-enhanced manipulation tasks. A recently introduced FingerVision sensor was shown capable o…
Entropic Regularization of Markov Decision Processes
Boris Belousov, Jan Peters
An optimal feedback controller for a given Markov decision process (MDP) can in principle be synthesized by value or policy iteration. However, if the system dynamics and the rewar…
Entropic Risk Measure in Policy Search
David Nass, Boris Belousov, Jan Peters
With the increasing pace of automation, modern robotic systems need to act in stochastic, non-stationary, partially observable environments. A range of algorithms for finding param…
f-Divergence constrained policy improvement
Boris Belousov, Jan Peters
To ensure stability of learning, state-of-the-art generalized policy iteration algorithms augment the policy improvement step with a trust region constraint bounding the informatio…