Menglu Tan — accepted AI-conference papers

2026

Unified Magnetic 5-DoF Localization Framework for Capsule Robots Via PMMN-DBO: From Single to Multi-Robot Scenarios with Real-Time Control–Localization Co-Design

Zijin Zeng, Chan Li, Zaiyang Chen, Shunxiao Huang, Wenyan Niu, Hongyan Sun +3

ICRA 2026poster

Motivated by clinical needs for precise navigation and safety, low-latency and high-precision localization has become a key enabler for capsule robots. A unified magnetic 5-DoF high-precision localization framework for capsule robots is presented. Building on layered multi-source magnetic field mode…

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2025

SRCNet: Super-resolution Networks for Capsule Endoscope Robots

Menglu Tan, Guangdong Zhan, Zijin Zeng, Ao Wang, Lin Feng

IROS 2025

In recent years, capsule robots have gained wide acceptance among doctors and patients for the examination of gastrointestinal diseases due to their non-invasive, safe, and painless advantages. However, the image resolution captured by capsule robots is limited by space size and power, which hinders

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2024

Dung Beetle Optimizer-based High-precision Localization for Magnetic-Controlled Capsule Robot

Zijin Zeng, Fengwu Wang, Chan Li, Menglu Tan, Shengyuan Wang, Lin Feng

IROS 2024poster

As a medical microrobot, magnetic-controlled capsule robots (MCRs) are pivotal in internal diagnostics and therapeutic interventions. Achieving high-precision localization of MCRs is essential for the successful execution of medical procedures. This paper introduces a novel Dung Beetle Optimizer (DB…

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