activity
20232026
most citedDecentralized Collective World Model for Emergent Communication and Coordination

4 citations · 5 across the 11 of their papers we have counts for

collaborators
Showing cs.ROShow all

6 papers · 1 filter

cs.RO2025

Haptic-Informed ACT with a Soft Gripper and Recovery-Informed Training for Pseudo Oocyte Manipulation

Pedro Miguel Uriguen Eljuri, Hironobu Shibata, Maeyama Katsuyoshi +2

In this paper, we introduce Haptic-Informed ACT, an advanced robotic system for pseudo oocyte manipulation, integrating multimodal information and Action Chunking with Transformers…

cs.RO2024

LiP-LLM: Integrating Linear Programming and dependency graph with Large Language Models for multi-robot task planning

Kazuma Obata, Tatsuya Aoki, Takato Horii +2

This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. In order for multiple robots to pe…

cs.RO2024

Goal Estimation-based Adaptive Shared Control for Brain-Machine Interfaces Remote Robot Navigation

Tomoka Muraoka, Tatsuya Aoki, Masayuki Hirata +3

In this study, we propose a shared control method for teleoperated mobile robots using brain-machine interfaces (BMI). The control commands generated through BMI for robot operatio…

cs.RO2024

Reflectance Estimation for Proximity Sensing by Vision-Language Models: Utilizing Distributional Semantics for Low-Level Cognition in Robotics

Masashi Osada, Gustavo A. Garcia Ricardez, Yosuke Suzuki +1

Large language models (LLMs) and vision-language models (VLMs) have been increasingly used in robotics for high-level cognition, but their use for low-level cognition, such as inte…

cs.RO2024

Stable Object Placing using Curl and Diff Features of Vision-based Tactile Sensors

Kuniyuki Takahashi, Shimpei Masuda, Tadahiro Taniguchi

Ensuring stable object placement is crucial to prevent objects from toppling over, breaking, or causing spills. When an object makes initial contact to a surface, and some force is…

cs.RO2024

A Contact Model based on Denoising Diffusion to Learn Variable Impedance Control for Contact-rich Manipulation

Masashi Okada, Mayumi Komatsu, Tadahiro Taniguchi

In this paper, a novel approach is proposed for learning robot control in contact-rich tasks such as wiping, by developing Diffusion Contact Model (DCM). Previous methods of learni…