8 papers
Embedded Inter-Subject Variability in Adversarial Learning for Inertial Sensor-Based Human Activity Recognition
Francisco M. Calatrava-Nicolás, Shoko Miyauchi, Vitor Fortes Rey +3
This paper addresses the problem of Human Activity Recognition (HAR) using data from wearable inertial sensors. An important challenge in HAR is the model's generalization capabili…
Single-View Shape Completion for Robotic Grasping in Clutter
Abhishek Kashyap, Yuxuan Yang, Henrik Andreasson +1
In vision-based robot manipulation, a single camera view can only capture one side of objects of interest, with additional occlusions in cluttered scenes further restricting visibi…
Can Context Bridge the Reality Gap? Sim-to-Real Transfer of Context-Aware Policies
Marco Iannotta, Yuxuan Yang, Johannes A. Stork +2
Sim-to-real transfer remains a major challenge in reinforcement learning (RL) for robotics, as policies trained in simulation often fail to generalize to the real world due to disc…
KEA: Keeping Exploration Alive by Proactively Coordinating Exploration Strategies
Shih-Min Yang, Martin Magnusson, Johannes A. Stork +1
Soft Actor-Critic (SAC) has achieved notable success in continuous control tasks but struggles in sparse reward settings, where infrequent rewards make efficient exploration challe…
Exploiting Radiance Fields for Grasp Generation on Novel Synthetic Views
Abhishek Kashyap, Henrik Andreasson, Todor Stoyanov
Vision based robot manipulation uses cameras to capture one or more images of a scene containing the objects to be manipulated. Taking multiple images can help if any object is occ…
Beyond Predefined Actions: Integrating Behavior Trees and Dynamic Movement Primitives for Robot Learning from Demonstration
David Cáceres DomÃnguez, Erik Schaffernicht, Todor Stoyanov
Interpretable policy representations like Behavior Trees (BTs) and Dynamic Motion Primitives (DMPs) enable robot skill transfer from human demonstrations, but each faces limitation…