4 citations · 4 across the 9 of their papers we have counts for
9 papers
Adapting Vision Foundation Models to Acoustics for Pose-Free 3D Sonar Reconstruction
Kevin Zhang, Jingxi Chen, Mohamad Qadri +5
Vision foundation models trained on Internet-scale RGB datasets enable remarkable capabilities across a range of tasks, from text-to-video generation to few-shot 3D scene reconstru…
Acoustic Neural 3D Reconstruction Under Pose Drift
Tianxiang Lin, Mohamad Qadri, Kevin Zhang +3
We consider the problem of optimizing neural implicit surfaces for 3D reconstruction using acoustic images collected with drifting sensor poses. The accuracy of current state-of-th…
Your Learned Constraint is Secretly a Backward Reachable Tube
Mohamad Qadri, Gokul Swamy, Jonathan Francis +2
Inverse Constraint Learning (ICL) is the problem of inferring constraints from safe (i.e., constraint-satisfying) demonstrations. The hope is that these inferred constraints can th…
BEVRender: Vision-based Cross-view Vehicle Registration in Off-road GNSS-denied Environment
Lihong Jin, Wei Dong, Wenshan Wang +1
We introduce BEVRender, a novel learning based approach for the localization of ground vehicles in Global Navigation Satellite System(GNSS)-denied off-road scenarios. These environ…
Z-Splat: Z-Axis Gaussian Splatting for Camera-Sonar Fusion
Ziyuan Qu, Omkar Vengurlekar, Mohamad Qadri +5
Differentiable 3D-Gaussian splatting (GS) is emerging as a prominent technique in computer vision and graphics for reconstructing 3D scenes. GS represents a scene as a set of 3D Ga…
AONeuS: A Neural Rendering Framework for Acoustic-Optical Sensor Fusion
Mohamad Qadri, Kevin Zhang, Akshay Hinduja +3
Underwater perception and 3D surface reconstruction are challenging problems with broad applications in construction, security, marine archaeology, and environmental monitoring. Tr…
Neural feels with neural fields: Visuo-tactile perception for in-hand manipulation
Sudharshan Suresh, Haozhi Qi, Tingfan Wu +9
To achieve human-level dexterity, robots must infer spatial awareness from multimodal sensing to reason over contact interactions. During in-hand manipulation of novel objects, suc…
Learning Covariances for Estimation with Constrained Bilevel Optimization
Mohamad Qadri, Zachary Manchester, Michael Kaess
We consider the problem of learning error covariance matrices for robotic state estimation. The convergence of a state estimator to the correct belief over the robot state is depen…
Learning Observation Models with Incremental Non-Differentiable Graph Optimizers in the Loop for Robotics State Estimation
Mohamad Qadri, Michael Kaess
We consider the problem of learning observation models for robot state estimation with incremental non-differentiable optimizers in the loop. Convergence to the correct belief over…