arXiv subjects

Jinhua Li

Publications and source records attributed to Jinhua Li.

3 recordsLinked to original sources

arXiv2026

A Rapid Instrument Exchange System for Humanoid Robots in Minimally Invasive Surgery

Humanoid robot technologies have demonstrated immense potential for minimally invasive surgery (MIS). Unlike dedicated multi-arm surgical platforms, the inherent dual-arm configuration of humanoid robots necessitates an efficient instrument exchange capability to perform complex procedures, mimicking the natural workflow where surgeons manually switch instruments. To address this, this paper proposes an immersive teleoperated rapid instrument exchange system. The system utilizes a low-latency mechanism based on single-axis compliant docking and environmental constraint release. Integrated with real-time first-person view (FPV) perception via a head-mounted display (HMD), this framework significantly reduces operational complexity and cognitive load during the docking process. Comparative evaluations between experts and novices demonstrate high operational robustness and a rapidly converging learning curve; novice performance in instrument attachment and detachment improved substantially after brief training. While long-distance spatial alignment still presents challenges in time cost and collaborative stability, this study successfully validates the technical feasibility of humanoid robots executing stable instrument exchanges within constrained clinical environments.

cs.RO↗

arXiv2025

Analytical and Neural Network Approaches for Solving Two-Dimensional Nonlinear Transient Heat Conduction

Accurately predicting nonlinear transient thermal fields in two-dimensional domains is a significant challenge in various engineering fields, where conventional analytical and numerical methods struggle to balance physical fidelity with computational efficiency when dealing with strong material nonlinearities and evolving multiphysics boundary conditions. To address this challenge, we propose a novel cross-disciplinary approach integrating Green's function formulations with adaptive neural operators, enabling a new paradigm for multiphysics thermal analysis. Our methodology combines rigorous analytical derivations with a physics-informed neural architecture consisting of five adaptive hidden layers (64 neurons per layer) that incorporates solutions as physical constraints, optimizing learning rates to balance convergence stability and computational speed. Extensive validation demonstrates superior performance in handling rapid thermal transients and strongly coupled nonlinear responses, which significantly improves computational efficiency while maintaining high agreement with analytical benchmarks across a range of material configurations and boundary conditions.

physics.comp-ph↗

arXiv2024

Persistent but weak magnetic field at Moon's midlife revealed by Chang'e-5 basalt

The evolution of the lunar magnetic field can reveal the Moon's interior structure, thermal history, and surface environment. The mid-to-late stage evolution of the lunar magnetic field is poorly constrained, and thus the existence of a long-lived lunar dynamo remains controversial. The Chang'e-5 mission returned the heretofore youngest mare basalts from Oceanus Procellarum uniquely positioned at mid-latitude. We recovered weak paleointensities of 2-4 uT from the Chang'e-5 basalt clasts at 2 billion years ago, attestting to the longevity of a lunar dynamo until at least the Moon's midlife. This paleomagnetic result implies the existence of thermal convection in the lunar deep interior at the lunar mid-stage which may have supplied mantle heat flux for the young volcanism.

physics.geo-ph↗