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Learning dexterous grasps that generalise to novel objects by combining hand and contact models.

, , , , , and . ICRA, page 5358-5365. IEEE, (2014)

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Combining active learning and reactive control for robot grasping., , , and . Robotics Auton. Syst., 58 (9): 1105-1116 (2010)Learning tactile characterizations of object- and pose-specific grasps., , and . IROS, page 1554-1560. IEEE, (2011)Learning Human Priors for Task-Constrained Grasping., , , and . ICVS, volume 9163 of Lecture Notes in Computer Science, page 207-217. Springer, (2015)Probabilistic consolidation of grasp experience., , , , , and . ICRA, page 193-200. IEEE, (2016)Domain Generalization for 6D Pose Estimation Through NeRF-based Image Synthesis., , and . CoRR, (2024)Task-oriented grasping with semantic and geometric scene understanding., , and . IROS, page 3266-3273. IEEE, (2017)Continuous Surface-Point Distributions for 3D Object Pose Estimation and Recognition., and . ACCV (3), volume 6494 of Lecture Notes in Computer Science, page 572-585. Springer, (2010)Learning of Multi-Dimensional, Multi-Modal Features for Robotic Grasping.. University of Liège, Belgium, (2010)End-to-end Neural Estimation of Spacecraft Pose with Intermediate Detection of Keypoints., , and . ECCV Workshops (1), volume 13801 of Lecture Notes in Computer Science, page 154-169. Springer, (2022)Modelling Primate Control of Grasping for Robotics Applications., , , , and . ECCV Workshops (2), volume 8926 of Lecture Notes in Computer Science, page 438-447. Springer, (2014)