Zhejiang, China

Sha Lu

This inventor holds 1 USPTO granted patent. Top assignee: Zhejiang University. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Sha Lu. Retrieved from https://idiyas.com/inventor/sha-lu-nvrsr6mb

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank

Average Co-Inventor Count = 1.0

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Sha Lu and Mobile Robot Place Re-Recognition

Introduction

Sha Lu is an inventor based in Zhejiang, China, associated with Zhejiang University. His listed patent focuses on helping mobile robots recognize previously visited places using lidar data.

Latest Patents

Lu is credited with 1 patent: “Method for Place Re-Recognition of Mobile Robot Based on Lidar Estimable Pose.” The method uses a Radon transform to represent rotation and translation changes as shifts in a sinusoidal graph. It then applies spectrum cross-correlation to estimate image translation and, in combination with the Radon transform, can determine relative rotation and translation. Translation-invariant information supports the creation of position descriptors for matching candidate locations. The approach also considers changing environments and uses a multi-channel bird’s-eye-view feature representation to improve how local features in lidar point clouds are represented.

Career Highlights

The available information identifies Lu’s work with Zhejiang University and highlights his contribution to lidar-based place recognition for mobile robots. The patent describes techniques for matching locations despite changes in viewpoint and environmental conditions.

Collaborations

Lu’s listed coworker is Xuecheng Xu. The patent information connects Lu’s work with Zhejiang University.

Conclusion

Sha Lu’s listed invention combines lidar-based feature representation and image-matching techniques to support reliable place re-recognition by mobile robots.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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