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Related papers: Tactile Object Pose Estimation from the First Touc…

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In this paper, we present Tac2Pose, an object-specific approach to tactile pose estimation from the first touch for known objects. Given the object geometry, we learn a tailored perception model in simulation that estimates a probability…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Maria Bauza , Antonia Bronars , Alberto Rodriguez

Robust object pose estimation is essential for manipulation and interaction tasks in robotics, particularly in scenarios where visual data is limited or sensitive to lighting, occlusions, and appearances. Tactile sensors often offer limited…

We're interested in the problem of estimating object states from touch during manipulation under occlusions. In this work, we address the problem of estimating object poses from touch during planar pushing. Vision-based tactile sensors…

Robotics · Computer Science 2021-03-30 Paloma Sodhi , Michael Kaess , Mustafa Mukadam , Stuart Anderson

Object pose estimation methods allow finding locations of objects in unstructured environments. This is a highly desired skill for autonomous robot manipulation as robots need to estimate the precise poses of the objects in order to…

Robotics · Computer Science 2022-03-22 Tarik Kelestemur , Robert Platt , Taskin Padir

In this paper, we address the problem of estimating the in-hand 6D pose of an object in contact with multiple vision-based tactile sensors. We reason on the possible spatial configurations of the sensors along the object surface.…

Robotics · Computer Science 2023-02-01 Gabriele M. Caddeo , Nicola A. Piga , Fabrizio Bottarel , Lorenzo Natale

In this paper, we propose a method for estimating in-hand object poses using proprioception and tactile feedback from a bimanual robotic system. Our method addresses the problem of reducing pose uncertainty through a sequence of frictional…

Robotics · Computer Science 2023-05-24 Andrea Sipos , Nima Fazeli

Joint estimation of grasped object pose and extrinsic contacts is central to robust and dexterous manipulation. In this paper, we propose a novel state-estimation algorithm that jointly estimates contact location and object pose in 3D using…

Robotics · Computer Science 2022-08-10 Andrea Sipos , Nima Fazeli

Prehensile autonomous manipulation, such as peg insertion, tool use, or assembly, require precise in-hand understanding of the object pose and the extrinsic contacts made during interactions. Providing accurate estimation of pose and…

Robotics · Computer Science 2026-01-01 Mark Van der Merwe , Kei Ota , Dmitry Berenson , Nima Fazeli , Devesh K. Jha

The connection between visual input and tactile sensing is critical for object manipulation tasks such as grasping and pushing. In this work, we introduce the challenging task of estimating a set of tactile physical properties from visual…

Computer Vision and Pattern Recognition · Computer Science 2021-09-22 Matthew Purri , Kristin Dana

This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either complete scene specifications or extrinsic sensor measurements,…

Tactile sensing provides a promising sensing modality for object pose estimation in manipulation settings where visual information is limited due to occlusion or environmental effects. However, efficiently leveraging tactile data for…

Tactile sensing has proven to be an invaluable tool for enhancing robotic perception, particularly in scenarios where visual data is limited or unavailable. However, traditional methods for pose estimation using tactile data often rely on…

Robotics · Computer Science 2024-09-24 Jose A. Eyzaguirre , Miquel Oller , Nima Fazeli

Tactile perception is central to robot manipulation in unstructured environments. However, it requires contact, and a mature implementation must infer object models while also accounting for the motion induced by the interaction. In this…

For certain manipulation tasks, object pose estimation from head-mounted cameras may not be sufficiently accurate. This is at least in part due to our inability to perfectly calibrate the coordinate frames of today's high degree of freedom…

Robotics · Computer Science 2022-04-12 Patrick Lancaster , Boling Yang , Joshua R. Smith

Humans rely on touch and tactile sensing for a lot of dexterous manipulation tasks. Our tactile sensing provides us with a lot of information regarding contact formations as well as geometric information about objects during any…

Robotics · Computer Science 2023-06-06 Kei Ota , Devesh K. Jha , Hsiao-Yu Tung , Joshua B. Tenenbaum

Accurate 3D pose estimation of grasped objects is an important prerequisite for robots to perform assembly or in-hand manipulation tasks, but object occlusion by the robot's own hand greatly increases the difficulty of this perceptual task.…

General robot manipulation requires the handling of previously unseen objects. Learning a physically accurate model at test time can provide significant benefits in data efficiency, predictability, and reuse between tasks. Tactile sensing…

Robotics · Computer Science 2026-02-26 Ethan K. Gordon , Bruke Baraki , Hien Bui , Michael Posa

The sense of touch plays a key role in enabling humans to understand and interact with surrounding environments. For robots, tactile sensing is also irreplaceable. While interacting with objects, tactile sensing provides useful information…

Robotics · Computer Science 2021-12-30 Jiaqi Jiang , Shan Luo

Touch sensing can help robots understand their sur- rounding environment, and in particular the objects they interact with. To this end, roboticists have, in the last few decades, developed several tactile sensing solutions, extensively…

Robotics · Computer Science 2017-11-13 Shan Luo , Joao Bimbo , Ravinder Dahiya , Hongbin Liu

Much of the literature on robotic perception focuses on the visual modality. Vision provides a global observation of a scene, making it broadly useful. However, in the domain of robotic manipulation, vision alone can sometimes prove…

Robotics · Computer Science 2019-03-11 Justin Lin , Roberto Calandra , Sergey Levine
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