sensor fusion | BestHub

Zhengtong Technical Team

Apr 15, 2025 · Artificial Intelligence

FAST‑LIO2 LiDAR‑IMU SLAM Implementation and Evaluation on Qiji Autonomous Patrol Vehicles

This article presents the technical background of SLAM, explains why GNSS‑based navigation fails in complex urban environments, describes the selection and testing of several LiDAR‑IMU SLAM algorithms—including FAST‑LIO2—on Qiji unmanned vehicles, and details the hardware configuration, algorithmic improvements, experimental workflow, and positioning results achieved in a real‑world patrol project.

FAST-LIO2LiDARRobotics

0 likes · 9 min read

FAST‑LIO2 LiDAR‑IMU SLAM Implementation and Evaluation on Qiji Autonomous Patrol Vehicles

HelloTech

Jun 6, 2024 · Mobile Development

Location Accuracy Issues and Optimization Strategies in Ride-Hailing Applications

The article examines ride‑hailing location failures—no fix and drift—explains Android vs iOS positioning, satellite and network sources, and presents a monitoring framework plus Wi‑Fi prompts and sensor‑fusion Kalman filtering that together reduce drift, improve accuracy, and boost order fulfillment.

GNSSKalman filterLocation Services

0 likes · 29 min read

Location Accuracy Issues and Optimization Strategies in Ride-Hailing Applications

Amap Tech

Dec 4, 2023 · Artificial Intelligence

End-to-End BEV+Transformer Perception and Modeling for High-Definition Map Production

By fusing LiDAR point clouds and camera images into a unified bird‑eye‑view space and applying Transformer‑based perception, multi‑sensor fusion, and graph‑diffusion modeling, the proposed BEV+Transformer framework automatically detects and smooths ground‑level line features and signs for high‑definition maps with centimeter‑level accuracy, boosting production efficiency and reducing cost.

BEVHD mapTransformer

0 likes · 20 min read

End-to-End BEV+Transformer Perception and Modeling for High-Definition Map Production

Tencent Tech

Apr 25, 2023 · Artificial Intelligence

How Tencent’s TRX‑Hand and TRX‑Arm Achieve Human‑like Dexterous Manipulation

On April 25, Tencent’s Robotics X lab unveiled its self‑developed TRX‑Hand and TRX‑Arm, a three‑finger dexterous hand and a seven‑degree‑of‑freedom arm that combine advanced hybrid actuation, high‑resolution tactile sensors, multi‑modal perception and real‑time planning to perform complex tasks such as cocktail mixing, object catching, and precise insertion.

AIRoboticsdexterous manipulation

0 likes · 10 min read

How Tencent’s TRX‑Hand and TRX‑Arm Achieve Human‑like Dexterous Manipulation

DataFunSummit

Oct 19, 2022 · Artificial Intelligence

Series Six of the Integer Intelligence Autonomous Driving Dataset Collection – Overview and Highlights

This article presents a comprehensive overview of several publicly available autonomous driving datasets, focusing on Series Six of the Integer Intelligence collection, which includes StreetLearn, UTBM RoboCar, Multi‑Vehicle Stereo Event Camera, comma2k19, the Annotated Laser Dataset, Ford, and Oxford RobotCar, detailing their sources, download links, publication years, key features, and research relevance.

Roboticsautonomous drivingcomputer vision

0 likes · 10 min read

Series Six of the Integer Intelligence Autonomous Driving Dataset Collection – Overview and Highlights

Amap Tech

Aug 18, 2021 · Fundamentals

Hardware Overview of High‑Precision Positioning and Orientation Systems

The article reviews the hardware of high‑precision positioning and orientation systems, explaining how GNSS and inertial measurement units (IMUs) are combined, describing sensor types, error sources, selection criteria, and testing methods needed to achieve centimeter‑level accuracy for mapping and mobility applications.

GNSSIMUhigh precision positioning

0 likes · 25 min read

Hardware Overview of High‑Precision Positioning and Orientation Systems

Architects' Tech Alliance

Jul 29, 2021 · Artificial Intelligence

L4 Autonomous Driving Technology: Architecture, Costs, and Commercial Applications

The article provides a comprehensive overview of L4 autonomous driving technology, detailing its perception‑decision‑execution architecture, sensor and computing requirements, cost considerations, commercial use cases, V2X communication, high‑precision mapping, and the broader industry outlook driven by AI, big data and IoT.

AIL4V2X

0 likes · 10 min read

L4 Autonomous Driving Technology: Architecture, Costs, and Commercial Applications

Amap Tech

Jul 9, 2021 · Fundamentals

GPS Time Synchronization: Principles, Methods, and Applications in Mapping Vehicles

GPS‑based time synchronization aligns camera, LiDAR, and inertial sensor streams in mapping vehicles by using the satellite‑derived Pulse‑Per‑Second signal and NMEA data to correct the MCU’s clock, handle PPS‑crystal and PPS‑NMEA anomalies, and provide sub‑microsecond timestamps for precise sensor fusion.

GPSNMEAPPS

0 likes · 11 min read

GPS Time Synchronization: Principles, Methods, and Applications in Mapping Vehicles

Architects' Tech Alliance

Apr 19, 2021 · Artificial Intelligence

Autonomous Driving Industry Research Report: Market Overview, Technology Landscape, and Growth Opportunities

This report provides a comprehensive overview of the autonomous driving industry, detailing the distinction between unmanned vehicles and ADAS, current market size and penetration, sensor technologies, policy influences, major players, and emerging opportunities for startups in perception and algorithm integration.

ADASAutomotive AIautonomous driving

0 likes · 9 min read

Autonomous Driving Industry Research Report: Market Overview, Technology Landscape, and Growth Opportunities

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

0 likes · 11 min read

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

Amap Tech

Jan 22, 2021 · Mobile Development

Design and Implementation of a DR+GNSS Playback Tool for Amap Car Navigation on Android

The article presents a DR + GNSS playback tool for Amap’s Android car‑navigation system that mimics sensor fusion via a custom AIDL protocol, supports existing log formats, runs in an independent process, and streamlines QA by cutting verification time from hours of road testing to under thirty minutes.

AndroidDRGNSS

0 likes · 10 min read

Design and Implementation of a DR+GNSS Playback Tool for Amap Car Navigation on Android

Didi Tech

Dec 29, 2020 · Artificial Intelligence

Evolution and Challenges of Perception in L4 Autonomous Driving

The article traces L4 autonomous-driving perception from early rule-based point-cloud methods through data-driven deep-learning models to emerging self-learning, multi-task systems, and highlights four key hurdles—model generalization and explainability, robust multi-sensor fusion, real-time compute limits, and proper uncertainty handling—calling for integrated AI, engineering, and data solutions.

AIautonomous drivingcomputer vision

0 likes · 12 min read

Evolution and Challenges of Perception in L4 Autonomous Driving

Amap Tech

Dec 24, 2020 · Artificial Intelligence

Advancing Mobile Navigation Accuracy: Lessons from the IPIN2020 Competition and VDR Technology

The Wuhan‑Amap team won IPIN2020’s vehicle‑navigation track by using big‑data mining and neural‑network‑enhanced Vehicle‑Dead Reckoning to fuse smartphone GNSS, IMU, and barometer data, overcoming GPS outages and sensor limitations, and demonstrating that machine‑learning‑driven inertial navigation can achieve vehicle‑grade accuracy on consumer phones.

Big DataIndoor PositioningVDR

0 likes · 8 min read

Advancing Mobile Navigation Accuracy: Lessons from the IPIN2020 Competition and VDR Technology

Didi Tech

Sep 10, 2020 · Artificial Intelligence

Technical Overview of DiDi's AR Indoor Navigation System

DiDi's AR indoor navigation system addresses GPS unreliability in large indoor venues by using SfM-based 3D reconstruction, robust visual localization with magnetometer/GNSS priors, and sensor fusion with pedestrian dead‑reckoning and deep‑learning heading estimation, cutting passenger pick‑up time by up to 25 % across dozens of airports and malls.

3D reconstructionAR navigationIndoor Positioning

0 likes · 19 min read

Technical Overview of DiDi's AR Indoor Navigation System

DataFunTalk

Mar 5, 2020 · Artificial Intelligence

High‑Precision Mapping and Localization Technologies for Autonomous Driving

This article explains the principles, components, generation process, and challenges of high‑precision topological and point‑cloud maps, and describes satellite‑based, map‑based, and fused high‑precision localization methods that underpin perception, prediction, planning, and control in autonomous driving systems.

SLAMautonomous drivinghigh-precision mapping

0 likes · 9 min read

High‑Precision Mapping and Localization Technologies for Autonomous Driving

DataFunTalk

Feb 13, 2020 · Artificial Intelligence

Deep Learning Techniques and Challenges in Autonomous Driving

This article reviews the rapid development of deep learning, its pivotal role in autonomous driving, outlines end‑to‑end perception‑to‑control pipelines, discusses the strengths and limitations of deep models, and proposes practical strategies such as task decomposition, multi‑method fusion, and sensor integration to improve safety and interpretability.

autonomous drivingcomputer visiondeep learning

0 likes · 8 min read

Deep Learning Techniques and Challenges in Autonomous Driving

DataFunTalk

Nov 27, 2019 · Artificial Intelligence

Front‑Fusion Based Recognition Pipeline for High‑Precision Map Static Obstacle Detection

This article presents a comprehensive front‑fusion recognition pipeline for high‑definition map static obstacle detection, detailing depth‑aware mapping, precise multi‑sensor calibration, point‑cloud registration, and semi‑supervised learning techniques that improve detection accuracy over traditional image‑only methods.

AIHD mapLiDAR

0 likes · 11 min read

Front‑Fusion Based Recognition Pipeline for High‑Precision Map Static Obstacle Detection

Amap Tech

Oct 31, 2019 · Artificial Intelligence

The Role of Digital Map Data in Enabling Automotive ADAS Systems

High‑quality digital map data augments traditional ADAS sensors by delivering super‑range, weather‑independent perception, centimeter‑level positioning, and detailed road context, enabling functions from speed‑limit reminders to full autonomy, standardized through ADASIS interfaces and exemplified by Gaode’s HD‑map solutions.

ADASAutomotiveautonomous driving

0 likes · 16 min read

The Role of Digital Map Data in Enabling Automotive ADAS Systems

DataFunTalk

Aug 13, 2019 · Artificial Intelligence

From L0 to L5: Building and Testing an Autonomous Driving System

This article explains how a conventional vehicle can be progressively upgraded through hardware retrofits, sensor integration, mapping, perception, control, and planning modules to achieve SAE Level 4/5 autonomy, using a step‑by‑step analogy with driver training and iterative testing.

AIautonomous drivingmapping

0 likes · 14 min read

From L0 to L5: Building and Testing an Autonomous Driving System

Amap Tech

Aug 13, 2019 · Artificial Intelligence

Multi‑Sensor Fusion Positioning for Vehicle Navigation: GPS/IMU/Map‑Matching Solution

Gaode's solution combines GPS, IMU, odometer, visual sensors with map‑matching using a Kalman filter, addressing yaw drift, loss of fix, and road‑capture errors in vehicle navigation, especially in urban canyons, achieving over 90% road identification and significant error reductions while keeping hardware costs low.

GNSSIMUKalman filter

0 likes · 16 min read

Multi‑Sensor Fusion Positioning for Vehicle Navigation: GPS/IMU/Map‑Matching Solution