activity
20222024
most citedSwitching Head-Tail Funnel UNITER for Dual Referring Expression Comprehension with Fetch-and-Carry Tasks

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2024

Nearest Neighbor Future Captioning: Generating Descriptions for Possible Collisions in Object Placement Tasks

Takumi Komatsu, Motonari Kambara, Shumpei Hatanaka +5

Domestic service robots (DSRs) that support people in everyday environments have been widely investigated. However, their ability to predict and describe future risks resulting fro…

cs.RO2024

Object Segmentation from Open-Vocabulary Manipulation Instructions Based on Optimal Transport Polygon Matching with Multimodal Foundation Models

Takayuki Nishimura, Katsuyuki Kuyo, Motonari Kambara +1

We consider the task of generating segmentation masks for the target object from an object manipulation instruction, which allows users to give open vocabulary instructions to dome…

cs.CV2023

DialMAT: Dialogue-Enabled Transformer with Moment-Based Adversarial Training

Kanta Kaneda, Ryosuke Korekata, Yuiga Wada +7

This paper focuses on the DialFRED task, which is the task of embodied instruction following in a setting where an agent can actively ask questions about the task. To address this…

cs.RO2023

Fully Automated Task Management for Generation, Execution, and Evaluation: A Framework for Fetch-and-Carry Tasks with Natural Language Instructions in Continuous Space

Motonari Kambara, Komei Sugiura

This paper aims to develop a framework that enables a robot to execute tasks based on visual information, in response to natural language instructions for Fetch-and-Carry with Obje…

cs.RO20232 cited

Switching Head-Tail Funnel UNITER for Dual Referring Expression Comprehension with Fetch-and-Carry Tasks

Ryosuke Korekata, Motonari Kambara, Yu Yoshida +4

This paper describes a domestic service robot (DSR) that fetches everyday objects and carries them to specified destinations according to free-form natural language instructions. G…

cs.RO2022

Relational Future Captioning Model for Explaining Likely Collisions in Daily Tasks

Motonari Kambara, Komei Sugiura

Domestic service robots that support daily tasks are a promising solution for elderly or disabled people. It is crucial for domestic service robots to explain the collision risk be…