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Zhengtong Technical Team
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
Python Programming Learning Circle
Python Programming Learning Circle
Apr 4, 2022 · Artificial Intelligence

Comprehensive Python Code Collection for Robot Algorithms: Localization, Mapping, SLAM, Path Planning, and Tracking

This article presents a curated collection of Python implementations for widely used robot algorithms—including EKF/UKF localization, histogram filtering, Gaussian grid mapping, various SLAM techniques, grid‑based and sampling‑based path planners, and multiple trajectory tracking controllers—along with usage instructions and visual demonstrations.

PythonRoboticsSLAM
0 likes · 11 min read
Comprehensive Python Code Collection for Robot Algorithms: Localization, Mapping, SLAM, Path Planning, and Tracking
Kuaishou Tech
Kuaishou Tech
Feb 9, 2022 · Mobile Development

Kuaishou Mobile Mixed Reality System: Architecture, Algorithms, and Applications

This article presents Kuaishou's mobile mixed reality (MR) system, detailing its integration of deep learning, SLAM, and scene reconstruction for real‑time spatial computing, the design of a monocular depth‑estimation model, a lightweight 3D rendering engine, and its deployment across iOS and Android devices with various user‑facing effects.

Depth EstimationKuaishouMixed Reality
0 likes · 16 min read
Kuaishou Mobile Mixed Reality System: Architecture, Algorithms, and Applications
Kuaishou Large Model
Kuaishou Large Model
Nov 26, 2021 · Artificial Intelligence

How Kuaishou’s ‘All‑Things AR’ Turns Real Objects into Interactive 3D Characters

‘All‑Things AR’ (万物AR) is a Kuaishou Y‑tech solution that lets users capture any real‑world object with a phone, automatically segments it using a custom AI model, and renders an animated 3D avatar via a lightweight SLAM‑based pipeline, enabling low‑cost, high‑quality AR experiences.

ARSLAMcomputer vision
0 likes · 16 min read
How Kuaishou’s ‘All‑Things AR’ Turns Real Objects into Interactive 3D Characters
Amap Tech
Amap Tech
Sep 24, 2020 · Artificial Intelligence

AR & Lane-Level Navigation Technology Evolution and Practice

In a 2020 Cloud Expo session, Alibaba Amap’s senior map expert Wang Qianwei detailed the evolution and practice of AR‑enabled lane‑level navigation, explaining how real‑time visual perception, cloud‑integrated high‑precision positioning (including MT‑SLAM) and fine‑grained 3‑D road models combine to deliver video‑augmented guidance, lane‑change alerts and traffic‑light status with roughly 30 cm accuracy.

AR navigationLane-Level NavigationSLAM
0 likes · 9 min read
AR & Lane-Level Navigation Technology Evolution and Practice
DataFunTalk
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
DataFunTalk
May 9, 2019 · Artificial Intelligence

High‑Definition Maps and Localization for Autonomous Driving: Concepts, Pipeline, and Challenges

This article presents a comprehensive overview of high‑definition mapping for autonomous vehicles, covering topological and 3D grid maps, the data‑collection and processing pipeline, key challenges such as cost and scalability, and detailed discussions of SLAM, pose‑graph optimization, ICP, and multi‑sensor localization techniques.

3D grid mapHD mapICP
0 likes · 18 min read
High‑Definition Maps and Localization for Autonomous Driving: Concepts, Pipeline, and Challenges
DataFunTalk
DataFunTalk
Mar 15, 2019 · Artificial Intelligence

A Comprehensive Overview of Deep Learning Applications in Computer Vision

This article provides an extensive review of deep learning techniques applied to computer vision, covering the evolution of CNN architectures, image and video processing tasks, 2.5‑D and 3‑D reconstruction, object detection, segmentation, tracking, SLAM, and various practical applications such as AR, content retrieval, and autonomous driving.

CNNSLAMcomputer vision
0 likes · 22 min read
A Comprehensive Overview of Deep Learning Applications in Computer Vision
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Apr 25, 2018 · Artificial Intelligence

How SLAM Powers Modern Robot Vacuums: From Sparse Maps to Vision‑Based Navigation

This article explains the fundamentals of SLAM technology, compares sparse, dense, and vision‑based approaches, evaluates four robot‑vacuum navigation schemes, presents test results across different scenarios, and discusses market opportunities for 360's laser‑SLAM driven vacuum cleaners.

AISLAMcomputer vision
0 likes · 11 min read
How SLAM Powers Modern Robot Vacuums: From Sparse Maps to Vision‑Based Navigation