2022年11月21日 · SLAM (simultaneous localization and mapping) is a method used for autonomous mobile robots (AMRs) that lets you build a map and localize your vehicle in that map at the same time. LiDAR (light detection and ranging) technology assists robots to navigate their surroundings through object perception, identification and collision avoidance.

5 天之前 · In this deep dive, we’ll explore how the integration of Kudan Visual SLAM and NVIDIA Isaac Perceptor is setting new performance standards for AMR perception, and driving the next leap in the evolution of autonomous robotics. Key highlights of what the blog entails: Advantages of 3D cameras over 2D LiDAR; Software architecture and key modules

2025年2月27日 · RTAB-MAP (Real-Time Appearance-Based Mapping) is employed for localization, integrating with an RGB-D camera and a 2D LiDAR for real-time localization and mapping. The navigation was performed using the A* algorithm for global path planning, combined with the Dynamic Window Approach (DWA) for local path planning.

2021年1月1日 · In this paper we suggest a Simultaneous Localization and Mapping (SLAM) algorithm for Autonomous Mobile Robots (AMRs) which have LiDAR (light detection and ranging) type planar sensors with low sampling rate, e.g., less than 1 Hz.

2024年9月4日 · As one of the core components of AMRs, LiDAR serves as the 'eyes' of the robot. LiDAR not only enables high-precision positioning and navigation but also provides real-time detection and identification of obstacles, ensuring reliable safety for AMR's obstacle avoidance.

This study addresses the development of a protection system employing LiDAR sensors and fuzzy logic to enable obstacle detection and avoidance for AMR-T. LiDAR sensors are utilized to gather spatial data, enabling real-time analysis of the surrounding environment.

More accurate and robust localization with Visual SLAM and/or 3D-Lidar SLAM against scenery changes and dynamic objects; Faster time-to-market compared to internal development or open-source based approach; Productivity improvement due to faster operation speed; Overall hardware cost reduction through lower grade sensors

5 天之前 · 重要なポイント: Kudan Visual SLAMとNVIDIA Isaac Perceptorの統合により、3Dカメラを活用して従来の2D LiDARシステムの限界を克服し、AMR向けにコスト効率が高く、堅牢で適応性のあるナビゲーションソリューションを提供します。 3. ソフトウェアアーキテクチャ

2024年10月1日 · The Q-Vision F540 is designed to overcome key obstacles that have traditionally hindered the widespread adoption of 3D LiDAR in AGV and AMR markets. It directly addresses issues such as: Limited field of view (FoV) and low resolution in existing iToF cameras; Lack of plug-and-play functionality, requiring extensive software development

We developed a 3D mapping system using the TFmini-S LiDAR sensor and an ATmega328P microcontroller. The system captures high-resolution spatial data, suitable for applications like autonomous navigation and environmental monitoring. The setup includes a stepper motor controlled by an A4988 driver for precise scanning.