4 citations · 4 across the 7 of their papers we have counts for
8 papers
Whose Is This?: Context-Aware Object Ownership Inference with Uncertainty-Guided Questioning
Saki Hashimoto, Akira Taniguchi, Shoichi Hasegawa +2
Service robots must infer object ownership to correctly interpret instructions such as "bring me my cup." However, ownership is a latent attribute that cannot be directly observed,…
On-Demand Human Assistance for Task Continuation under Physical Action Failures in LLM-based Planning
Shoichi Hasegawa, Akira Taniguchi, Lotfi El Hafi +2
While robot action planning based on large language models (LLMs) has advanced remarkably, continuing a task after a physical action failure during execution remains a key challeng…
Multi-Robot Task Planning for Multi-Object Retrieval Tasks with Distributed On-Site Knowledge via Large Language Models
Kento Murata, Shoichi Hasegawa, Tomochika Ishikawa +4
It is crucial to efficiently execute instructions such as "Find an apple and a banana" or "Get ready for a field trip," which require searching for multiple objects or understandin…
Toward Ownership Understanding of Objects: Active Question Generation with Large Language Model and Probabilistic Generative Model
Saki Hashimoto, Shoichi Hasegawa, Tomochika Ishikawa +4
Robots operating in domestic and office environments must understand object ownership to correctly execute instructions such as ``Bring me my cup.'' However, ownership cannot be re…
Take That for Me: Multimodal Exophora Resolution with Interactive Questioning for Ambiguous Out-of-View Instructions
Akira Oyama, Shoichi Hasegawa, Akira Taniguchi +2
Daily life support robots must interpret ambiguous verbal instructions involving demonstratives such as ``Bring me that cup,'' even when objects or users are out of the robot's vie…
Public Evaluation on Potential Social Impacts of Fully Autonomous Cybernetic Avatars for Physical Support in Daily-Life Environments: Large-Scale Demonstration and Survey at Avatar Land
Lotfi El Hafi, Kazuma Onishi, Shoichi Hasegawa +18
Cybernetic avatars (CAs) are key components of an avatar-symbiotic society, enabling individuals to overcome physical limitations through virtual agents and robotic assistants. Whi…
Object Instance Retrieval in Assistive Robotics: Leveraging Fine-Tuned SimSiam with Multi-View Images Based on 3D Semantic Map
Taichi Sakaguchi, Akira Taniguchi, Yoshinobu Hagiwara +3
Robots that assist humans in their daily lives should be able to locate specific instances of objects in an environment that match a user's desired objects. This task is known as i…
Real-world Instance-specific Image Goal Navigation: Bridging Domain Gaps via Contrastive Learning
Taichi Sakaguchi, Akira Taniguchi, Yoshinobu Hagiwara +3
Improving instance-specific image goal navigation (InstanceImageNav), which locates the identical object in a real-world environment from a query image, is essential for robotic sy…