Related papers: Sensorized gripper for human demonstrations
Recently, suction-based robotic systems with microscopic features or active suction components have been proposed to grip rough and irregular surfaces. However, sophisticated fabrication methods or complex control systems are required for…
The development of robotic grippers is driven by the need to execute particular manual tasks or meet specific objectives in handling operations. Grippers with specific functions vary from being small, accurate and highly controllable such…
Grasping a particular object may require a dedicated grasping movement that may also be specific to the robot end-effector. No generic and autonomous method does exist to generate these movements without making hypotheses on the robot or on…
We present placing via picking (PvP), a method to autonomously collect real-world demonstrations for a family of placing tasks in which objects must be manipulated to specific, contact-constrained locations. With PvP, we approach the…
Robot grasping is often formulated as a learning problem. With the increasing speed and quality of physics simulations, generating large-scale grasping data sets that feed learning algorithms is becoming more and more popular. An often…
In the robotic crop harvesting environment, foreign objects intrusion in the gripper workspace is frequently occurring and unignorable, however, rarely addressed. This paper presents a novel intelligent robotic grasping method capable of…
This paper introduces a novel robotic gripper, named as the SPD gripper. It features a palm and two mechanically identical and symmetrically arranged fingers, which can be driven independently or by a single motor. The fingertips of the…
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. We quantify the importance of…
In this work, we present a geometry-based grasping algorithm that is capable of efficiently generating both top and side grasps for unknown objects, using a single view RGB-D camera, and of selecting the most promising one. We demonstrate…
In this paper, we consider the problem of non-prehensile manipulation using grasped objects. This problem is a superset of many common manipulation skills including instances of tool-use (e.g., grasped spatula flipping a burger) and…
With the continuous advancement of robot teleoperation technology, shared control is used to reduce the physical and mental load of the operator in teleoperation system. This paper proposes an alternating shared control framework for object…
Compliant grippers enable robots to work with humans in unstructured environments. In general, these grippers can improve with tactile sensing to estimate the state of objects around them to precisely manipulate objects. However,…
Current approaches to grasp planning for robotics demonstrate high success rates, but degrade with noisy sensors and other factors. Previous works have proposed tactile-based grasp stability classifiers to detect failures, but these…
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,…
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…
Deep learning is an established framework for learning hierarchical data representations. While compute power is in abundance, one of the main challenges in applying this framework to robotic grasping has been obtaining the amount of data…
Telepresence is a necessity for present time as we can't reach everywhere and also it is useful in saving human life at dangerous places. A robot, which could be controlled from a distant location, can solve these problems. This could be…
Manipulation of deformable objects, such as ropes and cloth, is an important but challenging problem in robotics. We present a learning-based system where a robot takes as input a sequence of images of a human manipulating a rope from an…
The robotic handling of compliant and deformable food raw materials, characterized by high biological variation, complex geometrical 3D shapes, and mechanical structures and texture, is currently in huge demand in the ocean space,…
Many high precision (dis)assembly tasks are still being performed by humans, whereas this is an ideal opportunity for automation. This paper provides a framework which enables a non-expert human operator to teach a robotic arm to do complex…