← Search

Jiexin Xie

6 accepted papers

2026

CareBot-H: Enhancing Patient Transfer with Biomimetic Design and Trajectory Deformation Algorithm

ICRA 2026poster

This paper introduces the CareBot-H Robot, a humanoid nursing robot designed to perform patient transfer tasks in confined environments. The robot is equipped with biomimetic arms that replicate human arm size and function, and distributed tactile sensors that enhance operational safety during physi…

Cited by 0Scholar
2025

A Dual-Agent Collaboration Framework Based on LLMs for Nursing Robots to Perform Bimanual Coordination Tasks

RA-L 2025

Dual-arm coordination is a fundamental problem in humanoid nursing robot. Large language model (LLM)-driven dual-arm collaboration is gradually becoming a research hotspot in this field. However, the single-thread LLM task planner lacks the ability of co-scheduling, which leads to poor efficiency in

Cited by 9SourceScholar
2025

Enhancing Nursing and Elderly Care with Large Language Models: An AI-Driven Framework

COLING 2025main

This paper explores the application of large language models (LLMs) in nursing and elderly care, focusing on AI-driven patient monitoring and interaction. We introduce a novel Chinese nursing dataset and implement incremental pre-training (IPT) and supervised fine-tuning (SFT) techniques to enhance…

Cited by 2SourcePDFScholar
2022

A Training-Evaluation Method for Nursing Telerobot Operator with Unsupervised Trajectory Segmentation

IROS 2022poster

To cope with the difficulty of training and eval-uation for nursing telerobot operator. This paper proposes a training-evaluation method for operator with unsupervised trajectory segmentation. To evaluate the dexterity and proce-dural knowledge of the operators objectively, we propose a new unsuperv…

Cited by 2SourceScholar
2018

Unsupervised Trajectory Segmentation and Promoting of Multi-Modal Surgical Demonstrations

IROS 2018poster

To improve the efficiency of surgical trajectory segmentation for robot learning in robot-assisted minimally invasive surgery, this paper presents a fast unsupervised method using video and kinematic data, followed by a promoting procedure to address the over-segmentation issue. Unsupervised deep le…

Cited by 11SourceScholar