Prehensile Pushing: In-hand Manipulation with Push-Primitives

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ICRA 2018 - Stable Prehensile Pushing

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Stable Prehensile Pushing: In-Hand Manipulation with Alternating Sticking Contacts

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Planning Prehensile Pushing in the Horizontal Plane using RRT and Motion Cones

(4:12)

Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via DQL

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Humans, Robots, and Non-Prehensile Manipulation

(12:29)

Visual Foresight Tree for Object Retrieval from Clutter with Non-prehensile Rearrangement

(6:36)

Deep reinforcement learning for non-prehensile manipulation

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Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning

(5:6)

Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner

(1:6)

An Experimental Validation of Contact-Implicit Trajectory Optimization for Manipulation

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Evaluating the Quality of Non-Prehensile Balancing Grasps

(1:45)

Harnessing the Synergy between Pushing, Grasping, and Throwing for Object Manipulation in Cluttered

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Learning to push using Reinforcement Learning (IEEE Robotics and Automation Letters)

(2:59)

Learning Pneumatic Non-Prehensile Manipulation with a Mobile Blower

(6:56)

Target-driven Model Learning for Collision-aware Non-prehensile Holonomic Object Pushing

(2:33)

Learning Push-Grasping in Dense Clutter

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A Quasi-static Model and Simulation Approach for Pushing, Grasping, and Jamming | DAIR Lab

(1:24)

Semi-Autonomous Teleoperation via Learning Non-Prehensile Manipulation Skills, ICRA2022

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Learning with Planned Episodic Resets (LeaPER) for Non-Prehensile Rearrangement Manipulation.

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