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    STP1594

    3D Sensors on Driverless Trucks for Detection of Overhanging Objects in the Pathway

    Published: 2016


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    Abstract

    Human-operated and driverless trucks often collaborate in a mixed work space in industries and warehouses. This is more efficient and flexible than using only one kind of truck. However, because driverless trucks need to give way to driven trucks, a reliable detection system is required. Several challenges exist in the development of such a system. The first is to select interesting situations and objects. Overhanging objects are often found in industrial environments (e.g., tines on a forklift). Second is choosing a system that has the ability to detect those situations. (The traditional laser scanner situated two decimetres above the floor does not detect overhanging objects.) Third is to ensure that the perception system is reliable. A solution used on trucks today is to mount a two-dimensional laser scanner on top and tilt the scanner toward the floor. However, objects at the top of the truck will be detected too late, and a collision cannot always be avoided. Our aim is to replace the upper two-dimensional laser scanner with a three-dimensional camera, structural light, or time-of-flight (TOF) camera. It is important to maximize the field of view in the desired detection volume. Hence, the sensor placement is important. We conducted laboratory experiments to check and compare the various sensors' capabilities for different colors, using tines and a model of a tine in a controlled industrial environment. We also conducted field experiments in a warehouse. Our conclusion is that both the tested structural light and TOF sensors have problems detecting black items that are non-perpendicular to the sensor. It is important to optimize the light economy—meaning the illumination power, field of view, and exposure time—in order to detect as many different objects as possible.

    Keywords:

    mobile robots, safety, obstacle detection


    Author Information:

    Hedenberg, Klas
    University of Skövde, School of Engineering Science, Skövde,

    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad,


    Committee/Subcommittee: F45.03

    DOI: 10.1520/STP159420150051