5 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…
V3D-SLAM: Robust RGB-D SLAM in Dynamic Environments with 3D Semantic Geometry Voting
Tuan Dang, Khang Nguyen, Mandfred Huber
Simultaneous localization and mapping (SLAM) in highly dynamic environments is challenging due to the correlation complexity between moving objects and the camera pose. Many method…