high-precision map

Amap Tech

Jun 25, 2021 · Artificial Intelligence

Current Status and Future of High‑Precision Maps for Autonomous Driving

The Amap Technology Open Day video replay features Xiang Zhe presenting the current status and future of high‑precision maps for autonomous driving, covering autonomous‑driving evolution, map architecture, data collection, processing, production and update technologies, while offering contact details, a 20‑minute Q&A, and information on internship and full‑time positions.

AITechnical Talkautonomous driving

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Current Status and Future of High‑Precision Maps for Autonomous Driving

Amap Tech

Mar 12, 2021 · Artificial Intelligence

High‑Precision Maps for Autonomous Driving: Production System and Technical Insights

Gaode’s high‑precision map platform, described by GM Xiang Zhe, details a three‑stage production pipeline, multi‑layer map architecture, and tiered data‑collection strategy that together address city‑road challenges, ensure map freshness, advance positioning and perception algorithms, and support commercial Level‑4 autonomous‑driving deployments.

autonomous drivingdata collectionhigh-precision map

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High‑Precision Maps for Autonomous Driving: Production System and Technical Insights

Amap Tech

Oct 16, 2020 · Fundamentals

Fundamentals of High‑Precision Mapping and Coordinate Systems

The article explains high‑precision mapping fundamentals, from Earth’s ellipsoid and geoid definitions and common datums to 2‑D map projections, then details vehicle‑centred and sensor coordinate frames (ECEF, ENU, body, LiDAR, IMU, camera), their transformations, rotation representations, and key standards such as EPSG and Proj.4.

Coordinate SystemsECEFGIS

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Fundamentals of High‑Precision Mapping and Coordinate Systems

Amap Tech

Nov 14, 2019 · Artificial Intelligence

Technical Evolution of Ground Marking Recognition for High‑Precision Maps

AMap’s ground‑marking recognition has progressed from simple threshold methods to advanced deep‑learning pipelines—including two‑stage R‑FCN, cascade detectors with local regression, corner‑point and segmentation hybrids, and LiDAR‑based 3‑D PointRCNN—achieving over 99 % recall and sub‑5 cm positional accuracy for high‑precision map production.

Deep Learningcomputer visionground marking

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Technical Evolution of Ground Marking Recognition for High‑Precision Maps