Improving AGV obstacle avoidance with HySLAM
Challenge
SLAM technology for autonomous navigation
GPS is an important component for autonomous vehicles to be able to position themselves in the world. However, this is not always easy in covered areas, where another method of localisation is required. With SLAM (Simultaneous Localisation and Mapping), a device can simultaneously map its surroundings and position itself within them.
Technologies
From greenhouses to warehouses and lawns
The applications are wide-ranging. For example, the technology has already been used at Flanders Make for harvest prediction in strawberry cultivation: drones follow rows of plants, detect flowers and locate them on a 3D map. But the same approach can also be used for autonomous mobile robots (AMRs) in warehouses, robot vacuum cleaners or inspection robots in industrial environments, all without the need for GPS.
Situational and self-awareness technologies
To identify, interrogate, and evaluate both environmental conditions and system states.
Result
Precision, flexibility and low cost
SLAM makes it possible to combine affordable hardware with advanced image analysis, enabling autonomous vehicles and drones to navigate accurately in complex environments. The technology can be used flexibly in a wide range of sectors, from agriculture to logistics and infrastructure management.
