ROBOTICS g Mark Davidson of DreamVu, an early-
stage 3D vision company, agreed that no single technology can meet all the requirements for AMRs. ‘Tere’s no single sensor solution out there,’ he said. ‘Te challenge is finding the perfect combination and making sure the different systems work together effectively.’ DreamVu’s omnidirectional optical
sensor looks like an upside-down coffee filter, with a series of curved surfaces that capture light for each point in the field of view at multiple vantage points. Powerful algorithms convert the raw data into two RGB panoramas that offer a 360° view over distances of up to five metres, and from these images traditional stereo depth techniques allow distances to be calculated with an accuracy of one per cent for objects that are one metre away. ‘Our technology gives AMR robot designers
the largest field of view as well as accurate depth information to create the most complete map of the robot’s surroundings,’ said Davidson. But he cautioned that the optimal performance is achieved by combining this 3D information with a lidar system that can reliably provide accurate distances over a longer range. ‘Tat way we get the accuracy of lidar as well as the situational awareness of a camera,’ he said. Of course, the cameras and sensors are
just the eyes of the AMR. Powerful data processing algorithms are needed for the robot to work out where it is, create a map of its surroundings, and follow a set navigational rules. Te ability to make autonomous decisions also requires the addition of machine learning algorithms that enable the robot to evaluate the best course of action. Here, again, there are compromises to
be made. ‘We need powerful computer processors to analyse the data and enable the robot to react quickly enough, but we
‘For electric vehicles it’s very important to be able to move the car body from one location to another’
also need to embed them on a mobile platform with limited access to electrical power,’ said Adam. ‘A bigger battery is needed to power a strong vision system with lots of onboard capabilities, but that places limitations on the size and agility of the robot.’ For sensor manufacturers such as Sick
and DreamVu, there is a clear preference among AMR developers for cameras with embedded processors. ‘At the software level, customers are always keen to have a plug- and-play device,’ said Sherman. ‘Tey don’t care about the technology, they just want to know that the robot can navigate in a reliable way. Tat means we need to provide on-board software to evaluate the visual information and decide which route to take.’ Davidson agreed. ‘While the sensor itself
becomes more expensive, customers want more of the workflow to be done within the camera,’ he said. ‘Tat reduces the workload for the host computer on the AMR, and requires less integration and less synchronisation between the different sensors that are deployed on the robot.’ But a central computing system is likely
to be needed to support more advanced AI applications, particularly when fleets of AMRs are moving around a manufacturing facility at the same time. Tis will require significant computational resources to collect such large amounts of data, analyse them using sophisticated machine learning algorithms, and relay instructions to the robots quickly enough for it to react.
As well as powerful processing
capabilities, such deployments demand a high-bandwidth wireless communications channel for sending and receiving information. ‘So far we have had to rely on WiFi, but that has limited bandwidth and supports only limited mobility,’ said Adam. ‘5G technology will be a real game- changer, because it will make it possible to send an order and receive a response much more quickly.’ As a result, Omron now has a partnership with Nokia to develop 5G technology specifically for mobile robots. ‘We already have a few pilot plants testing this technology, and it looks really promising,’ he added. Omron currently sells around 70 per
The PAL omnidirectional image sensor from DreamVu has a series of curved surfaces that capture light from all directions at multiple points on the sensor. This is converted into two RGB panoramic images from which distances can be calculated
14 IMAGING AND MACHINE VISION EUROPE DECEMBER 2021/JANUARY 2022
cent of its AMRs into the automotive sector, although during the pandemic interest has grown in applications such as food and commodities, as well as disinfection. But current deployments remain small in scale, with manufacturers still working out how they can derive most value from an emerging technology that remains relatively expensive. ‘We are still in the innovation domain,’ said Adam. ‘Our customers know they need
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