se (3)-tracknet: Data-driven 6d pose tracking by calibrating image residuals in synthetic domains

B Wen, C Mitash, B Ren… - 2020 IEEE/RSJ …, 2020‏ - ieeexplore.ieee.org
Tracking the 6D pose of objects in video sequences is important for robot manipulation. This
task, however, introduces multiple challenges:(i) robot manipulation involves significant …

Survey of learning-based approaches for robotic in-hand manipulation

AI Weinberg, A Shirizly, O Azulay… - Frontiers in Robotics and …, 2024‏ - frontiersin.org
Human dexterity is an invaluable capability for precise manipulation of objects in complex
tasks. The capability of robots to similarly grasp and perform in-hand manipulation of objects …

A survey on the integration of machine learning with sampling-based motion planning

T McMahon, A Sivaramakrishnan… - … and Trends® in …, 2022‏ - nowpublishers.com
Sampling-based methods are widely adopted solutions for robot motion planning. The
methods are straightforward to implement, effective in practice for many robotic systems. It is …

Robust, occlusion-aware pose estimation for objects grasped by adaptive hands

B Wen, C Mitash, S Soorian, A Kimmel… - … on Robotics and …, 2020‏ - ieeexplore.ieee.org
Many manipulation tasks, such as placement or within-hand manipulation, require the
object's pose relative to a robot hand. The task is difficult when the hand significantly …

Adaptive synchronization of uncertain underactuated Euler–Lagrange agents

T Tao, S Roy, B De Schutter… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
This article proposes a framework for adaptive synchronization of uncertain underactuated
Euler–Lagrange (EL) agents. The designed distributed controller can handle both state …

Learning haptic-based object pose estimation for in-hand manipulation control with underactuated robotic hands

O Azulay, I Ben-David, A Sintov - IEEE Transactions on Haptics, 2022‏ - ieeexplore.ieee.org
Unlike traditional robotic hands, underactuated compliant hands are challenging to model
due to inherent uncertainties. Consequently, pose estimation of a grasped object is usually …

A probabilistic model for planar sliding of objects with unknown material properties: Identification and robust planning

C Song, A Boularias - … on Intelligent Robots and Systems (IROS …, 2020‏ - ieeexplore.ieee.org
This paper introduces a new technique for learning probabilistic models of mass and friction
distributions of unknown objects, and performing robust sliding actions by using the learned …

The blindfolded traveler's problem: A search framework for motion planning with contact estimates

B Saund, S Choudhury, S Srinivasa… - … Journal of Robotics …, 2023‏ - journals.sagepub.com
We address the problem of robot motion planning under uncertainty where the only
observations are through contact with the environment. Such problems are typically solved …

Motion planning with competency-aware transition models for underactuated adaptive hands

A Sintov, A Kimmel, KE Bekris… - 2020 IEEE International …, 2020‏ - ieeexplore.ieee.org
Underactuated adaptive hands simplify gras** tasks but it is difficult to model their
interactions with objects during in-hand manipulation. Learned data-driven models have …

Learning to transfer dynamic models of underactuated soft robotic hands

L Schramm, A Sintov, A Boularias - 2020 IEEE International …, 2020‏ - ieeexplore.ieee.org
Transfer learning is a popular approach to bypassing data limitations in one domain by
leveraging data from another domain. This is especially useful in robotics, as it allows …