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In this work, we address a challenging problem of fine-grained and coarse-grained recognition of object manipulation actions. Due to the variations in geometrical and motion constraints, there are different manipulations actions possible to…

Computer Vision and Pattern Recognition · Computer Science 2018-06-21 Kartik Gupta , Darius Burschka , Arnav Bhavsar

This thesis is concerned with deriving planning algorithms for robot manipulators. Manipulation has two effects, the robot has a physical effect on the object, and it also acquires information about the object. This thesis presents…

Robotics · Computer Science 2022-01-20 Claudio Zito

In this work, we present a grasp planner which integrates two sources of information to generate robust grasps for a robotic hand. First, the topological information of the object model is incorporated by building the mean curvature…

Robotics · Computer Science 2017-10-09 Nikolaus Vahrenkamp , Eduard Koch , Mirko Waechter , Tamim Asfour

Robot-to-human handovers often rely on static, open-loop strategies (or, at best, approaches that adapt only the position), which generally do not consider how the object will be grasped by the human, thus requiring the user to adapt. This…

Robotics · Computer Science 2026-04-27 Federico Biagi , Dario Onfiani , Simone Silenzi , Cristina Iani , Luigi Biagiotti

In this paper we propose an approach for efficient grasp selection for manipulation tasks of unknown objects. Even for simple tasks such as pick-and-place, a unique solution is rare to occur. Rather, multiple candidate grasps must be…

Robotics · Computer Science 2016-03-15 Ana Huaman Quispe , Heni Ben Amor , Henrik Christensen , Mike Stilman

Humans excel at grasping objects and manipulating them. Capturing human grasps is important for understanding grasping behavior and reconstructing it realistically in Virtual Reality (VR). However, grasp capture - capturing the pose of a…

Computer Vision and Pattern Recognition · Computer Science 2019-07-18 Samarth Brahmbhatt , Charles C. Kemp , James Hays

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 in the vicinity of an already applied grasp. Our method…

Robotics · Computer Science 2017-04-20 Emil Hyttinen , Danica Kragic , Renaud Detry

We propose a robotic manipulation system that can pivot objects on a surface using vision, wrist force and tactile sensing. We aim to control the rotation of an object around the grip point of a parallel gripper by allowing rotational slip,…

Robotics · Computer Science 2023-10-09 Shiyu Xu , Tianyuan Liu , Michael Wong , Dana Kulić , Akansel Cosgun

In this paper we explore state-of-the-art underactuated, compliant robot gripper designs through looking at their performance on a generic grasping task. Starting from a state of the art open gripper design, we propose design…

Robotics · Computer Science 2016-01-19 Eduardo Ruiz , Walterio Mayol-Cuevas

To achieve a successful grasp, gripper attributes such as its geometry and kinematics play a role as important as the object geometry. The majority of previous work has focused on developing grasp methods that generalize over novel object…

Rotational displacement about the grasping point is a common grasp failure when an object is grasped at a location away from its center of gravity. Tactile sensors with soft surfaces, such as GelSight sensors, can detect the rotation…

Robotics · Computer Science 2021-08-03 Raj Kolamuri , Zilin Si , Yufan Zhang , Arpit Agarwal , Wenzhen Yuan

Grasp planning and estimation have been a longstanding research problem in robotics, with two main approaches to find graspable poses on the objects: 1) geometric approach, which relies on 3D models of objects and the gripper to estimate…

Robotics · Computer Science 2025-04-11 Xun Tu , Karthik Desingh

In this paper, we study the problem of adapting manipulation trajectories involving grasped objects (e.g. tools) defined for a single grasp pose to novel grasp poses. A common approach to address this is to define a new trajectory for each…

Robotics · Computer Science 2024-08-02 Georgios Papagiannis , Kamil Dreczkowski , Vitalis Vosylius , Edward Johns

Humans exhibit outstanding learning, planning and adaptation capabilities while performing different types of industrial tasks. Given some knowledge about the task requirements, humans are able to plan their limbs motion in anticipation of…

Robotics · Computer Science 2020-08-06 Noémie Jaquier , Leonel Rozo , Sylvain Calinon

In this paper, we explore whether a robot can learn to regrasp a diverse set of objects to achieve various desired grasp poses. Regrasping is needed whenever a robot's current grasp pose fails to perform desired manipulation tasks. Endowing…

Robotics · Computer Science 2021-11-18 Shuo Cheng , Kaichun Mo , Lin Shao

We introduce a large-scale dataset named MultiGripperGrasp for robotic grasping. Our dataset contains 30.4M grasps from 11 grippers for 345 objects. These grippers range from two-finger grippers to five-finger grippers, including a human…

Robotics · Computer Science 2024-08-29 Luis Felipe Casas , Ninad Khargonkar , Balakrishnan Prabhakaran , Yu Xiang

Visual Object tracking research has undergone significant improvement in the past few years. The emergence of tracking by detection approach in tracking paradigm has been quite successful in many ways. Recently, deep convolutional neural…

Computer Vision and Pattern Recognition · Computer Science 2017-11-23 Litu Rout , Sidhartha , Gorthi R. K. S. S. Manyam , Deepak Mishra

The human gaze is an important cue to signal intention, attention, distraction, and the regions of interest in the immediate surroundings. Gaze tracking can transform how robots perceive, understand, and react to people, enabling new modes…

Robotics · Computer Science 2024-06-11 Tim Schreiter , Andrey Rudenko , Martin Magnusson , Achim J. Lilienthal

Despite the enormous progress and generalization in robotic grasping in recent years, existing methods have yet to scale and generalize task-oriented grasping to the same extent. This is largely due to the scale of the datasets both in…

Robotics · Computer Science 2020-11-16 Adithyavairavan Murali , Weiyu Liu , Kenneth Marino , Sonia Chernova , Abhinav Gupta

We consider the problem of reorienting a rigid object with arbitrary known shape on a table using a two-finger pinch gripper. Reorienting problem is challenging because of its non-smoothness and high dimensionality. In this work, we focus…

Robotics · Computer Science 2019-12-06 Yifan Hou , Zhenzhong Jia , Matthew T. Mason