Search Results - "Handa, Ankur"

Why pediatric cardiology in India? by Handa, Ankur

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SceneNet RGB-D: Can 5M Synthetic Images Beat Generic ImageNet Pre-training on Indoor Segmentation? by McCormac, John, Handa, Ankur, Leutenegger, Stefan, Davison, Andrew J.

“…We introduce SceneNet RGB-D, a dataset providing pixel-perfect ground truth for scene understanding problems such as semantic segmentation, instance…”
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Pediatric cardiac procedures in India: Who bears the cost? by Faisal, Nabeel Valappil, Handa, Ankur, Ramakrishnan, Sivasubramanian

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A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM by Handa, Ankur, Whelan, Thomas, McDonald, John, Davison, Andrew J.

“…We introduce the Imperial College London and National University of Ireland Maynooth (ICL-NUIM) dataset for the evaluation of visual odometry, 3D…”
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Understanding RealWorld Indoor Scenes with Synthetic Data by Handa, Ankur, Patraucean, Viorica, Badrinarayanan, Vijay, Stent, Simon, Cipolla, Roberto

“…Scene understanding is a prerequisite to many high level tasks for any automated intelligent machine operating in real world environments. Recent attempts with…”
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Sim2Real in Robotics and Automation: Applications and Challenges by Hofer, Sebastian, Bekris, Kostas, Handa, Ankur, Gamboa, Juan Camilo, Mozifian, Melissa, Golemo, Florian, Atkeson, Chris, Fox, Dieter, Goldberg, Ken, Leonard, John, Karen Liu, C., Peters, Jan, Song, Shuran, Welinder, Peter, White, Martha

“…To Perform reliably and consistently over sustained periods of time, large-scale automation critically relies on computer simulation. Simulation allows us and…”
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ContactGrasp: Functional Multi-finger Grasp Synthesis from Contact by Brahmbhatt, Samarth, Handa, Ankur, Hays, James, Fox, Dieter

“…Grasping and manipulating objects is an important human skill. Since most objects are designed to be manipulated by human hands, anthropomorphic hands can…”
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SemanticFusion: Dense 3D semantic mapping with convolutional neural networks by McCormac, John, Handa, Ankur, Davison, Andrew, Leutenegger, Stefan

“…Ever more robust, accurate and detailed mapping using visual sensing has proven to be an enabling factor for mobile robots across a wide variety of…”
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DexYCB: A Benchmark for Capturing Hand Grasping of Objects by Chao, Yu-Wei, Yang, Wei, Xiang, Yu, Molchanov, Pavlo, Handa, Ankur, Tremblay, Jonathan, Narang, Yashraj S., Van Wyk, Karl, Iqbal, Umar, Birchfield, Stan, Kautz, Jan, Fox, Dieter

“…We introduce DexYCB, a new dataset for capturing hand grasping of objects. We first compare DexYCB with a related one through cross-dataset evaluation. We then…”
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Domain Randomization and Generative Models for Robotic Grasping by Tobin, Josh, Biewald, Lukas, Duan, Rocky, Andrychowicz, Marcin, Handa, Ankur, Kumar, Vikash, McGrew, Bob, Ray, Alex, Schneider, Jonas, Welinder, Peter, Zaremba, Wojciech, Abbeel, Pieter

“…Deep learning-based robotic grasping has made significant progress thanks to algorithmic improvements and increased data availability. However,…”
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Model-Based Generalization Under Parameter Uncertainty Using Path Integral Control by Abraham, Ian, Handa, Ankur, Ratliff, Nathan, Lowrey, Kendall, Murphey, Todd D., Fox, Dieter

“…This letter addresses the problem of robot interaction in complex environments where online control and adaptation is necessary. By expanding the sample space…”
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Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience by Chebotar, Yevgen, Handa, Ankur, Makoviychuk, Viktor, Macklin, Miles, Issac, Jan, Ratliff, Nathan, Fox, Dieter

“…We consider the problem of transferring policies to the real world by training on a distribution of simulated scenarios. Rather than manually tuning the…”
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Proximal tubular aortopulmonary window in an adult - A diagnostic dilemma solved by cardiac computed tomographic angiography by Singh, Resham, Ojha, Vineeta, Nagulakonda, Sravan, Malhi, Amarinder Singh, Handa, Ankur, Kumar, Sanjeev

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Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger by Allshire, Arthur, MittaI, Mayank, Lodaya, Varun, Makoviychuk, Viktor, Makoviichuk, Denys, Widmaier, Felix, Wuthrich, Manuel, Bauer, Stefan, Handa, Ankur, Garg, Animesh

“…In-hand manipulation of objects is an important capability to enable robots to carry-out tasks which demand high levels of dexterity. This work presents a…”
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SceneNet: An annotated model generator for indoor scene understanding by Handa, Ankur, Patraucean, Viorica, Stent, Simon, Cipolla, Roberto

“…We introduce SceneNet, a framework for generating high-quality annotated 3D scenes to aid indoor scene understanding. SceneNet leverages manually-annotated…”
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DexPilot: Vision-Based Teleoperation of Dexterous Robotic Hand-Arm System by Handa, Ankur, Van Wyk, Karl, Yang, Wei, Liang, Jacky, Chao, Yu-Wei, Wan, Qian, Birchfield, Stan, Ratliff, Nathan, Fox, Dieter

“…Teleoperation offers the possibility of imparting robotic systems with sophisticated reasoning skills, intuition, and creativity to perform tasks. However,…”
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Analysing high frame-rate camera tracking by Handa, Ankur

“…High frame-rate offers benefits of robust and accurate camera tracking for rapid motion. However, the benefits are generally understated arguing that it is not…”
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Robust Learning of Tactile Force Estimation through Robot Interaction by Sundaralingam, Balakumar, Lambert, Alexander Sasha, Handa, Ankur, Boots, Byron, Hermans, Tucker, Birchfield, Stan, Ratliff, Nathan, Fox, Dieter

“…Current methods for estimating force from tactile sensor signals are either inaccurate analytic models or task-specific learned models. In this paper, we…”
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DexPBT: Scaling up Dexterous Manipulation for Hand-Arm Systems with Population Based Training by Petrenko, Aleksei, Allshire, Arthur, State, Gavriel, Handa, Ankur, Makoviychuk, Viktor

“…In this work, we propose algorithms and methods that enable learning dexterous object manipulation using simulated one- or two-armed robots equipped with…”
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Learning Latent Space Dynamics for Tactile Servoing by Sutanto, Giovanni, Ratliff, Nathan, Sundaralingam, Balakumar, Chebotar, Yevgen, Su, Zhe, Handa, Ankur, Fox, Dieter

“…To achieve a dexterous robotic manipulation, we need to endow our robot with tactile feedback capability, i.e. the ability to drive action based on tactile…”
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