Waterloo, Canada

Abhishank Gaba

This inventor holds 1 USPTO granted patent. Top assignee: Avidbots Corp. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Abhishank Gaba. Retrieved from https://idiyas.com/inventor/abhishank-gaba

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

Calculating rank

% Patents Active = 100.0

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Abhishank Gaba and Semantic Segmentation for Cleaning Devices.

Introduction

Abhishank Gaba is an inventor based in Waterloo, Canada. His work includes a patent for improving how autonomous and semi-autonomous cleaning devices perceive and avoid obstacles.

Latest Patents

Gaba is associated with 1 patent: “System and Method of Semantic Segmentation for a Cleaning Device.” The invention uses machine learning and visual data to train an algorithm, such as a deep neural network, to distinguish ground from non-ground areas. A cleaning device can use this information in its path planning to avoid obstacles, including cardboard boxes, low pallets, and forklift tines. This semantic-segmentation approach adds another layer to the device’s perception-based safety protocols.

Career Highlights

Gaba works at Avidbots Corp., a company developing autonomous cleaning technology. His patented work addresses a practical challenge in that field: helping cleaning devices identify low-height obstacles that may be difficult to detect and avoid.

Collaborations

Gaba’s listed coworkers include Ali Jahani and Egor Bredikhin. Their shared connection to Avidbots places the invention within a broader company environment focused on autonomous cleaning systems.

Conclusion

Abhishank Gaba’s patent applies machine learning and visual perception to obstacle avoidance, supporting safer navigation for autonomous and semi-autonomous cleaning devices.

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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