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The expansion of mobile robots from indoor to outdoor environments is a significant technological breakthrough, involving numerous technical challenges and innovations. This transition requires robots to not only adapt to various environmental conditions but also overcome a range of issues, from navigation and perception to battery life. With the ongoing evolution of robotics, we are witnessing some innovative solutions that enable robots to seamlessly transition between or operate in both...

Point cloud detection refers to the process of capturing 3D spatial data through sensors like LiDAR, forming a "point cloud" where each point represents a measurement from an object’s surface. Traditional point cloud detection allows robots to perceive obstacles, walls, and objects, aiding navigation and obstacle avoidance. However, point cloud data primarily provides geometric information about space, lacking deeper semantic understanding of the environment. Semantic understanding, a more advanced technology,...

In the early days of robotics, particularly in autonomous driving and warehouse logistics, robots relied heavily on high-precision maps for localization and navigation. These maps, created using LiDAR, high-definition cameras, and other sensors, captured environmental details such as walls, obstacles, and roads. However, while high-precision maps performed well in known environments, they had significant limitations: High costs of map creation and updates; Limited adaptability to environmental changes (e.g., temporary obstacles,...

How is markerless navigation achieved? It relies on a series of innovative technologies. Let’s break it down into the following key aspects: High-Precision Localization and Navigation The core of markerless navigation is that robots can achieve high-precision localization without relying on any external markers, using SLAM (Simultaneous Localization and Mapping) technology. SLAM allows robots to build environmental maps in real-time and localize themselves, without the need for pre-set maps or...