Modern industries face two critical challenges: A shrinking labor force and demands for increased productivity in industrial settings. Autonomous mobile robots have emerged as the Industry 4.0 solutions to these problems. But, their functionality still faces limitations. Improving obstacle detection for mobile robots is one of the keys to unlocking their potential.
ifm leverages decades of innovation and expertise to create state-of-the-art obstacle detection systems. Our solutions help make mobile robots more efficient and accurate. This in turn makes them economically-accessible for more businesses.
Our solution can robustly detect small objects on the ground, such as fork tines, due to its robust floor segmentation.
Better object recognition and spatial awareness means fewer unplanned stops that require human intervention. This results in more missions completed each day.
Increased throughput makes a robot more valuable to the end-user. With BoM costs for AMRs remaining relatively static, reducing the number of units necessary for the job reduces CapEx for the customer.
Obstacle detection is the ability to sense and adapt to obstructions in its desire path plan. In mobile robot automation, sensing technology and algorithms detect objects, walls, and other obstructions.
Early obstacle detection systems sent light signals or laser beams across a two-dimensional plane. They identified obstacles blocking the beam’s path. Robots then required human intervention when the system encountered an obstruction.
Today’s detection systems allow robots to better understand their surroundings. This increased perception allows for better decision-making during path planning.
Thanks to decades of improvements, obstacle detection systems easily identify objects in the path of a robot. But newer technology gathers much more information. As a result, avoiding false positives is now the crucial focus.
A false positive is when the system flags an obstacle when there’s none. This phenomenon often occurs when the software can’t distinguish between the floor and an object or a reflection from the environment (e.g. shiny metal or dust).
That results in less efficiency and increased downtime. The robot stops for no reason and requires human intervention to resume its route.
Avoiding false positives is one of ifm’s main concentrations for improving obstacle detection systems.
Overall Equipment Effectiveness (OEE) is an essential key indicator of Industry 4.0 implementations. This is a measure of manufacturing productivity consisting of 3 factors.
ifm’s ODS directly impacts the robots OEE score by increasing:
Availability is increased when unplanned stops are decreased.
Performance is increased with a better understanding of the environment.
Each robot's OEE increases by reducing the overall number of unplanned stops. When each robot is more efficient, a facility needs less of them to complete their throughput demands.
Obstacle detection is key to making automated mobile robots more accessible to mid-size companies and more enterprise-level businesses. As the technology improves, obstacle detection systems will enable AMRs to have fewer unplanned stops, leading to more efficient missions.
Today, ifm concentrates on both the physics engines behind 3D cameras and indirect time of flight systems as well as solutions that enable more efficient operation of the mobile robot.