activity
20132026
most citedData-Driven Grasp Synthesis - A Survey

881 citations · 1.6k across the 66 of their papers we have counts for

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Showing 2017Show all

7 papers · 1 filter

cs.RO2017★ 1 cited

A Decomposition-Based Approach to Reasoning about Free Space Path-Connectivity for Rigid Objects in 2D

Anastasiia Varava, J. Frederico Carvalho, Danica Kragic +1

In this paper, we compute a conservative approximation of the path-connected components of the free space of a rigid object in a 2D workspace in order to solve two closely related…

cs.RO2017★ 19 cited

Human-Robot Collaboration: From Psychology to Social Robotics

Judith Bütepage, Danica Kragic

With the advances in robotic technology, research in human-robot collaboration (HRC) has gained in importance. For robots to interact with humans autonomously they need active deci…

cs.RO2017★ 1 cited

Estimating Tactile Data for Adaptive Grasping of Novel Objects

Emil Hyttinen, Danica Kragic, Renaud Detry

We present an adaptive grasping method that finds stable grasps on novel objects. The main contributions of this paper is in the computation of the probability of success of grasps…

cs.RO2017★ 16 cited

Deep Predictive Policy Training using Reinforcement Learning

Ali Ghadirzadeh, Atsuto Maki, Danica Kragic +1

Skilled robot task learning is best implemented by predictive action policies due to the inherent latency of sensorimotor processes. However, training such predictive policies is c…

cs.RO2017★ 35 cited

Reinforcement Learning for Pivoting Task

Rika Antonova, Silvia Cruciani, Christian Smith +1

In this work we propose an approach to learn a robust policy for solving the pivoting task. Recently, several model-free continuous control algorithms were shown to learn successfu…

cs.RO2017★ 19 cited

Anticipating many futures: Online human motion prediction and synthesis for human-robot collaboration

Judith Bütepage, Hedvig Kjellström, Danica Kragic

Fluent and safe interactions of humans and robots require both partners to anticipate the others' actions. A common approach to human intention inference is to model specific traje…