Dex-net 1.0: A cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards
This paper presents the Dexterity Network (Dex-Net) 1.0, a dataset of 3D object models and
a sampling-based planning algorithm to explore how Cloud Robotics can be used for robust …
a sampling-based planning algorithm to explore how Cloud Robotics can be used for robust …
Deep learning a grasp function for grasping under gripper pose uncertainty
E Johns, S Leutenegger… - 2016 IEEE/RSJ …, 2016 - ieeexplore.ieee.org
This paper presents a new method for parallel-jaw grasping of isolated objects from depth
images, under large gripper pose uncertainty. Whilst most approaches aim to predict the …
images, under large gripper pose uncertainty. Whilst most approaches aim to predict the …
One-shot imitation learning via interaction warping
Imitation learning of robot policies from few demonstrations is crucial in open-ended
applications. We propose a new method, Interaction Warping, for learning SE (3) robotic …
applications. We propose a new method, Interaction Warping, for learning SE (3) robotic …
Transferring grasping skills to novel instances by latent space non-rigid registration
D Rodriguez, C Cogswell, S Koo… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Robots acting in open environments need to be able to handle novel objects. Based on the
observation that objects within a category are often similar in their shapes and usage, we …
observation that objects within a category are often similar in their shapes and usage, we …
Task-informed grasping of partially observed objects
In this letter, we address the problem of task-informed grasping in scenarios where only
incomplete or partial object information is available. Existing methods, which either focus on …
incomplete or partial object information is available. Existing methods, which either focus on …
Transferring category-based functional grasping skills by latent space non-rigid registration
D Rodriguez, S Behnke - IEEE Robotics and Automation …, 2018 - ieeexplore.ieee.org
Objects within a category are often similar in their shape and usage. When we-as humans-
want to grasp something, we transfer our knowledge from past experiences and adapt it to …
want to grasp something, we transfer our knowledge from past experiences and adapt it to …
Learning generalizable tool use with non-rigid grasp-pose registration
Tool use, a hallmark feature of human intelligence, remains a challenging problem in
robotics due the complex contacts and high-dimensional action space. In this work, we …
robotics due the complex contacts and high-dimensional action space. In this work, we …
Combining Shape Completion and Grasp Prediction for Fast and Versatile Grasping with a Multi-Fingered Hand
M Humt, D Winkelbauer, U Hillenbrand… - 2023 IEEE-RAS 22nd …, 2023 - ieeexplore.ieee.org
Grasping objects with limited or no prior knowledge about them is a highly relevant skill in
assistive robotics. Still, in this general setting, it has remained an open problem, especially …
assistive robotics. Still, in this general setting, it has remained an open problem, especially …
Transferring grasp configurations using active learning and local replanning
H Tian, C Wang, D Manocha… - … conference on robotics …, 2019 - ieeexplore.ieee.org
We present a new approach to transfer grasp configurations from prior example objects to
novel objects. We assume the novel and example objects have the same topology and …
novel objects. We assume the novel and example objects have the same topology and …
Autonomous dual-arm manipulation of familiar objects
Autonomous dual-arm manipulation is an essential skill to deploy robots in unstructured
scenarios. However, this is a challenging undertaking, particularly in terms of perception and …
scenarios. However, this is a challenging undertaking, particularly in terms of perception and …