Obstacle detection adds significant value to AMRs. It overcomes common AMR challenges and enhances robot capabilities by enabling autonomous movement and collision avoidance in environments like warehouses or manufacturing facilities.

The performance of ODS is best described through the detection of real-world obstacles. The videos below were recorded in the ifm warehouse utilizing the O3R Perception platform and a small mobile robot .

The right obstacle detection system will enhance your robot’s value for end-users by increasing throughput. Learn how ifm’s ODS gives you the competitive edge.

ifm O3R系列 3D ToF相机 应用于全球知名物流方案提供商Knapp的AMR产品。3D空间避障，托盘定位检测，一套3D相机，实现两个应用。

AMR（Autonomous Mobile Robot，自主移动机器人）是一种无需外部轨道、磁条或二维码辅助，就能在复杂环境中自主完成任务的智能机器人。 SLAM技术：利用 激光雷达 、 深度摄像头 等传感器，实时构建环境地图，规划最优路线。 AI算法：自主决策避障、路径优化，甚至能在任务冲突时“权衡利弊”。 AGV需要依赖外部导航设备，像火车跑铁轨；而AMR就像一台带导航系统的出租车，哪里需要跑哪里，随叫随到。 AGV适合固定路径和重复任务，而AMR则适合动态场景和复 …

AMR（Autonomous Mobile Robot）即自主移动机器人，“广义”上是指自主性很强的移动机器人。 自主性很弱的移动机器人（如遥控机器人，沿着导轨走的移动机器人等）都不能称作AMR，只有自主性很强（能对环境中各种动态变化做出自己的合理反应）的移动机器人（如非遥控的无人机，无人驾驶汽车等）才能被称作AMR。 而这里我们所说的“AMR行业”，仅仅“狭义”上指室内AMR和半室外AMR。 AMR的概念源自机器人技术科研领域，承载着科学家们对移动机器人技术发展的期 …

2017年1月19日 · This repository contains various ROS packages that allows you to interface with your Omron AMR Mobile Robot via the ROS environment. For Point Cloud-based Obstacle Avoidance, check the branch obs_avoidance_devel. To find the developer's guide, click Here. On information pertaining to robot to camera calibration, see Here.

Below are two examples of mounting positions for ODS. The first example shows a typical AMR platform, with one camera on each side. In this example, each camera is an O3R225, which has a wide opening angle and minimizes the blind spots around the vehicle. The four cameras create 3D obstacle awareness around the vehicle.

The O3R obstacle detection system is a unified, mult-modal platform. It seamlessly integrates multiple cameras to address complex mobile robotics challenges.

The O3R-ODS performance depends upon various factor: this whitepaper gives an introduction to the factors influencing ODS performance and how the system can be tested and evaluated for benchmarking. Factors to be considered