Search Results - "Journal of robotics"

Learning dexterous in-hand manipulation by Andrychowicz, OpenAI: Marcin, Baker, Bowen, Chociej, Maciek, Józefowicz, Rafal, McGrew, Bob, Pachocki, Jakub, Petron, Arthur, Plappert, Matthias, Powell, Glenn, Ray, Alex, Schneider, Jonas, Sidor, Szymon, Tobin, Josh, Welinder, Peter, Weng, Lilian, Zaremba, Wojciech

“…We use reinforcement learning (RL) to learn dexterous in-hand manipulation policies that can perform vision-based object reorientation on a physical Shadow…”
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How to train your robot with deep reinforcement learning: lessons we have learned by Ibarz, Julian, Tan, Jie, Finn, Chelsea, Kalakrishnan, Mrinal, Pastor, Peter, Levine, Sergey

“…Deep reinforcement learning (RL) has emerged as a promising approach for autonomously acquiring complex behaviors from low-level sensor observations. Although…”
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Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection by Levine, Sergey, Pastor, Peter, Krizhevsky, Alex, Ibarz, Julian, Quillen, Deirdre

“…We describe a learning-based approach to hand-eye coordination for robotic grasping from monocular images. To learn hand-eye coordination for grasping, we…”
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Human motion trajectory prediction: a survey by Rudenko, Andrey, Palmieri, Luigi, Herman, Michael, Kitani, Kris M, Gavrila, Dariu M, Arras, Kai O

“…With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand, and anticipate human…”
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1 year, 1000 km: The Oxford RobotCar dataset by Maddern, Will, Pascoe, Geoffrey, Linegar, Chris, Newman, Paul

“…We present a challenging new dataset for autonomous driving: the Oxford RobotCar Dataset. Over the period of May 2014 to December 2015 we traversed a route…”
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Kimera: From SLAM to spatial perception with 3D dynamic scene graphs by Rosinol, Antoni, Violette, Andrew, Abate, Marcus, Hughes, Nathan, Chang, Yun, Shi, Jingnan, Gupta, Arjun, Carlone, Luca

“…Humans are able to form a complex mental model of the environment they move in. This mental model captures geometric and semantic aspects of the scene,…”
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Robotic manipulation and sensing of deformable objects in domestic and industrial applications: a survey by Sanchez, Jose, Corrales, Juan-Antonio, Bouzgarrou, Belhassen-Chedli, Mezouar, Youcef

“…We present a survey of recent work on robot manipulation and sensing of deformable objects, a field with relevant applications in diverse industries such as…”
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Learning robust, real-time, reactive robotic grasping by Morrison, Douglas, Corke, Peter, Leitner, Jürgen

“…We present a novel approach to perform object-independent grasp synthesis from depth images via deep neural networks. Our generative grasping convolutional…”
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Real-time dynamics of soft and continuum robots based on Cosserat rod models by Till, John, Aloi, Vincent, Rucker, Caleb

“…The dynamic equations of many continuum and soft robot designs can be succinctly formulated as a set of partial differential equations (PDEs) based on…”
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Keyframe-based visual–inertial odometry using nonlinear optimization by Leutenegger, Stefan, Lynen, Simon, Bosse, Michael, Siegwart, Roland, Furgale, Paul

“…Combining visual and inertial measurements has become popular in mobile robotics, since the two sensing modalities offer complementary characteristics that…”
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SE-Sync: A certifiably correct algorithm for synchronization over the special Euclidean group by Rosen, David M, Carlone, Luca, Bandeira, Afonso S, Leonard, John J

“…Many important geometric estimation problems naturally take the form of synchronization over the special Euclidean group: estimate the values of a set of…”
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Iterated extended Kalman filter based visual-inertial odometry using direct photometric feedback by Bloesch, Michael, Burri, Michael, Omari, Sammy, Hutter, Marco, Siegwart, Roland

“…This paper presents a visual-inertial odometry framework that tightly fuses inertial measurements with visual data from one or more cameras, by means of an…”
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Contact-aided invariant extended Kalman filtering for robot state estimation by Hartley, Ross, Ghaffari, Maani, Eustice, Ryan M, Grizzle, Jessy W

“…Legged robots require knowledge of pose and velocity in order to maintain stability and execute walking paths. Current solutions either rely on vision data,…”
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Vision meets robotics: The KITTI dataset by Geiger, A, Lenz, P, Stiller, C, Urtasun, R

“…We present a novel dataset captured from a VW station wagon for use in mobile robotics and autonomous driving research. In total, we recorded 6 hours of…”
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The limits and potentials of deep learning for robotics by Sünderhauf, Niko, Brock, Oliver, Scheirer, Walter, Hadsell, Raia, Fox, Dieter, Leitner, Jürgen, Upcroft, Ben, Abbeel, Pieter, Burgard, Wolfram, Milford, Michael, Corke, Peter

“…The application of deep learning in robotics leads to very specific problems and research questions that are typically not addressed by the computer vision and…”
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The EuRoC micro aerial vehicle datasets by Burri, Michael, Nikolic, Janosch, Gohl, Pascal, Schneider, Thomas, Rehder, Joern, Omari, Sammy, Achtelik, Markus W, Siegwart, Roland

“…This paper presents visual-inertial datasets collected on-board a micro aerial vehicle. The datasets contain synchronized stereo images, IMU measurements and…”
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Cable manipulation with a tactile-reactive gripper by She, Yu, Wang, Shaoxiong, Dong, Siyuan, Sunil, Neha, Rodriguez, Alberto, Adelson, Edward

“…Cables are complex, high-dimensional, and dynamic objects. Standard approaches to manipulate them often rely on conservative strategies that involve long…”
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Paris-Lille-3D: A large and high-quality ground-truth urban point cloud dataset for automatic segmentation and classification by Roynard, Xavier, Deschaud, Jean-Emmanuel, Goulette, François

“…This paper introduces a new urban point cloud dataset for automatic segmentation and classification acquired by mobile laser scanning (MLS). We describe how…”
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Model-based dynamic feedback control of a planar soft robot: trajectory tracking and interaction with the environment by Della Santina, Cosimo, Katzschmann, Robert K, Bicchi, Antonio, Rus, Daniela

“…Leveraging the elastic bodies of soft robots promises to enable the execution of dynamic motions as well as compliant and safe interaction with an unstructured…”
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Reinforcement learning in robotics: A survey by Kober, Jens, Bagnell, J. Andrew, Peters, Jan

“…Reinforcement learning offers to robotics a framework and set of tools for the design of sophisticated and hard-to-engineer behaviors. Conversely, the…”
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