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Few-shot adaptation is an important capability for intelligent robots that perform tasks in open-world settings such as everyday environments or flexible production. In this paper, we propose a novel approach for non-prehensile manipulation…

Robotics · Computer Science 2025-04-01 Fabian Baumeister , Lukas Mack , Joerg Stueckler

Fast neuromorphic event-based vision sensors (Dynamic Vision Sensor, DVS) can be combined with slower conventional frame-based sensors to enable higher-quality inter-frame interpolation than traditional methods relying on fixed motion…

Computer Vision and Pattern Recognition · Computer Science 2021-12-20 Adam Radomski , Andreas Georgiou , Thomas Debrunner , Chenghan Li , Luca Longinotti , Minwon Seo , Moosung Kwak , Chang-Woo Shin , Paul K. J. Park , Hyunsurk Eric Ryu , Kynan Eng

Differentiable simulators promise faster computation time for reinforcement learning by replacing zeroth-order gradient estimates of a stochastic objective with an estimate based on first-order gradients. However, it is yet unclear what…

Machine Learning · Computer Science 2022-08-23 H. J. Terry Suh , Max Simchowitz , Kaiqing Zhang , Russ Tedrake

Real-time motion generation -- which is essential for achieving reactive and adaptive behavior -- under kinodynamic constraints for high-dimensional systems is a crucial yet challenging problem. We address this with a two-step approach:…

Robotics · Computer Science 2025-07-25 Yonghyeon Lee

Molecular simulation technologies have afforded researchers a unique look into the nanoscale interactions driving physical processes. However, a limitation for molecular dynamics (MD) simulations is that they must be performed on…

Computational Physics · Physics 2022-09-22 Martin Kulke , Josh V Vermaas

We address the issue of physical implausibility in multi-view neural reconstruction. While implicit representations have gained popularity in multi-view 3D reconstruction, previous work struggles to yield physically plausible results,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Junfeng Ni , Yixin Chen , Bohan Jing , Nan Jiang , Bin Wang , Bo Dai , Puhao Li , Yixin Zhu , Song-Chun Zhu , Siyuan Huang

Recent work has shown the ability to learn generative models for 3D shapes from only unstructured 2D images. However, training such models requires differentiating through the rasterization step of the rendering process, therefore past work…

Computer Vision and Pattern Recognition · Computer Science 2020-03-02 Sebastian Lunz , Yingzhen Li , Andrew Fitzgibbon , Nate Kushman

We consider the problem of simultaneous control and parameter estimation when the model is available only as a differentiable physics simulator. We propose a receding-horizon control framework in which a model predictive control (MPC)…

Optimization and Control · Mathematics 2026-04-07 Alan Williams , Alp Sunol

The challenge of markerless human motion tracking is the high dimensionality of the search space. Thus, efficient exploration in the search space is of great significance. In this paper, a motion capturing algorithm is proposed for upper…

Computer Vision and Pattern Recognition · Computer Science 2020-02-25 Ziyuan Liu , Dongheui Lee , Wolfgang Sepp

Differential Dynamic Programming (DDP) is an efficient computational tool for solving nonlinear optimal control problems. It was originally designed as a single shooting method and thus is sensitive to the initial guess supplied. This work…

Robotics · Computer Science 2023-09-29 He Li , Wenhao Yu , Tingnan Zhang , Patrick M. Wensing

Advances in markerless motion capture are expanding access to biomechanical movement analysis, making it feasible to obtain high-quality movement data from outpatient clinics, inpatient hospitals, therapy, and even home. Expanding access to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Ruize Yang , Ann Kennedy , R. James Cotton

Reconstructing biomechanically realistic 3D human motion - recovering both kinematics (motion) and kinetics (forces) - is a critical challenge. While marker-based systems are lab-bound and slow, popular monocular methods use oversimplified,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Farnoosh Koleini , Hongfei Xue , Ahmed Helmy , Pu Wang

This work proposes a novel motion guided method for target-less self-calibration of a LiDAR and camera and use the re-projection of LiDAR points onto the image reference frame for real-time depth upsampling. The calibration parameters are…

Computer Vision and Pattern Recognition · Computer Science 2020-07-06 Juan Castorena , Gint Puskorius , Gaurav Pandey

Robot design optimization, imitation learning and system identification share a common problem which requires optimization over robot or task parameters at the same time as optimizing the robot motion. To solve these problems, we can use…

Robotics · Computer Science 2022-09-05 Traiko Dinev , Carlos Mastalli , Vladimir Ivan , Steve Tonneau , Sethu Vijayakumar

Fiducial markers have been broadly used to identify objects or embed messages that can be detected by a camera. Primarily, existing detection methods assume that markers are printed on ideally planar surfaces. Markers often fail to be…

Computer Vision and Pattern Recognition · Computer Science 2022-06-17 Mustafa B. Yaldiz , Andreas Meuleman , Hyeonjoong Jang , Hyunho Ha , Min H. Kim

We present differentiable particle filters (DPFs): a differentiable implementation of the particle filter algorithm with learnable motion and measurement models. Since DPFs are end-to-end differentiable, we can efficiently train their…

Machine Learning · Computer Science 2018-05-31 Rico Jonschkowski , Divyam Rastogi , Oliver Brock

Meshfree simulation methods are emerging as compelling alternatives to conventional mesh-based approaches, particularly in the fields of Computational Fluid Dynamics (CFD) and continuum mechanics. In this publication, we provide a…

Machine Learning · Computer Science 2024-03-21 Paulami Banerjee , Mohan Padmanabha , Chaitanya Sanghavi , Isabel Michel , Simone Gramsch

Metasurfaces are subwavelength-structured artificial media that can shape and localize electromagnetic waves in unique ways. The inverse design of these devices is a non-convex optimization problem in a high dimensional space, making global…

Computational Physics · Physics 2019-11-22 Jiaqi Jiang , Jonathan A. Fan

Molecular dynamics simulations produce data with complex nonlinear dynamics. If the timestep behavior of such a dynamic system can be represented by a linear operator, future states can be inferred directly without expensive simulations.…

Machine Learning · Computer Science 2021-05-27 Willis Hoke , Daniel Shea , Stephen Casey

Estimation techniques to precisely localize a kinematic platform with GNSS observables can be broadly partitioned into two categories: differential, or undifferenced. The differential techniques (e.g., real-time kinematic (RTK)) have…

Robotics · Computer Science 2018-08-01 Ryan M. Watson , Jason N. Gross
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