4 papers
DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation
Tien Pham, Xinyun Chi, Khang Nguyen +2
Reinforcement learning (RL) agents can learn to solve complex tasks from visual inputs, but generalizing these learned skills to new environments remains a major challenge in RL ap…
FlowMP: Learning Motion Fields for Robot Planning with Conditional Flow Matching
Khang Nguyen, An T. Le, Tien Pham +3
Prior flow matching methods in robotics have primarily learned velocity fields to morph one distribution of trajectories into another. In this work, we extend flow matching to capt…
Distortion-Aware Adversarial Attacks on Bounding Boxes of Object Detectors
Pham Phuc, Son Vuong, Khang Nguyen +1
Deep learning-based object detection has become ubiquitous in the last decade due to its high accuracy in many real-world applications. With this growing trend, these models are in…
Volumetric Mapping with Panoptic Refinement via Kernel Density Estimation for Mobile Robots
Khang Nguyen, Tuan Dang, Manfred Huber
Reconstructing three-dimensional (3D) scenes with semantic understanding is vital in many robotic applications. Robots need to identify which objects, along with their positions an…