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se (3)-tracknet: Data-driven 6d pose tracking by calibrating image residuals in synthetic domains
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 …
task, however, introduces multiple challenges:(i) robot manipulation involves significant …
Survey of learning-based approaches for robotic in-hand manipulation
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 …
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
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 …
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
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 …
object's pose relative to a robot hand. The task is difficult when the hand significantly …
Adaptive synchronization of uncertain underactuated Euler–Lagrange agents
This article proposes a framework for adaptive synchronization of uncertain underactuated
Euler–Lagrange (EL) agents. The designed distributed controller can handle both state …
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
Unlike traditional robotic hands, underactuated compliant hands are challenging to model
due to inherent uncertainties. Consequently, pose estimation of a grasped object is usually …
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
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 …
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
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 …
observations are through contact with the environment. Such problems are typically solved …
Motion planning with competency-aware transition models for underactuated adaptive hands
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 …
interactions with objects during in-hand manipulation. Learned data-driven models have …
Learning to transfer dynamic models of underactuated soft robotic hands
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 …
leveraging data from another domain. This is especially useful in robotics, as it allows …