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20172026
most citedLearning Efficient Policies for Picking Entangled Wire Harnesses: An Approach to Industrial Bin Picking

41 citations · 104 across the 35 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.RO2025

A Flexible Field-Based Policy Learning Framework for Diverse Robotic Systems and Sensors

Jose Gustavo Buenaventura Carreon, Floris Erich, Roman Mykhailyshyn +3

We present a cross robot visuomotor learning framework that integrates diffusion policy based control with 3D semantic scene representations from D3Fields to enable category level…

cs.CV2025

Prompt2Craft: Generating Functional Craft Assemblies with LLMs

Vitor Hideyo Isume, Takuya Kiyokawa, Natsuki Yamanobe +3

Inspired by traditional handmade crafts, where a person improvises assemblies based on the available objects, we formally introduce the Craft Assembly Task. It is a robotic assembl…

cs.RO2025

RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments

Masaki Murooka, Tomohiro Motoda, Ryoichi Nakajo +5

We present RoboManipBaselines, an open-source software framework for imitation learning research in robotic manipulation. The framework supports the entire imitation learning pipel…

cs.RO2025

Self-Augmented Robot Trajectory: Efficient Imitation Learning via Safe Self-augmentation with Demonstrator-annotated Precision

Hanbit Oh, Masaki Murooka, Tomohiro Motoda +2

Imitation learning is a promising paradigm for training robot agents; however, standard approaches typically require substantial data acquisition -- via numerous demonstrations or…

cs.CV2025

NeuralMeshing: Complete Object Mesh Extraction from Casual Captures

Floris Erich, Naoya Chiba, Abdullah Mustafa +4

How can we extract complete geometric models of objects that we encounter in our daily life, without having access to commercial 3D scanners? In this paper we present an automated…

cs.RO2025

Visual Prompting for Robotic Manipulation with Annotation-Guided Pick-and-Place Using ACT

Muhammad A. Muttaqien, Tomohiro Motoda, Ryo Hanai +1

Robotic pick-and-place tasks in convenience stores pose challenges due to dense object arrangements, occlusions, and variations in object properties such as color, shape, size, and…