Keep your distance: Relative position key to industrial jobs

March 28, 2016  - By

Operating in industrial environments, where no margin for error is tolerated, is complex, stressful and delicate. The distance from an in-flight UAV to the industrial asset that it is observing or inspecting obviously has critical importance for safety, data precision and cost-effectiveness. The AiRobot Ranger counters this problem by displaying the distance between the UAV and the object of interest on multiple smart phones or tablets, ensuring the extra situational awareness that is crucial for professional UAV operations.

The Ranger consists of an add-on sensor module that can be easily attached and detached, a ground station and iOS/Android apps. Everyone involved in an operation can simultaneously log in on the ground station to receive real-time situational feedback. In adition to visual feedback, the Ranger also offers audio feedback, via voice commands, beep tones and adjustable target zones.

Passive and independent, the system does not require connection with flight controller or other UAV electronics. It can be mounted externally on most industrial UAVs.

Airborne Ranger (top left) continuously monitors the distance between itself and the silo, transmitting the separation to pilot and payload operator (foreground).

Airborne Ranger (top left) continuously monitors the distance between itself and the silo, transmitting the separation to pilot and payload operator (foreground).

Silo Inspection. To gather data concerning defects or damage to an agricultural products silo, a Ranger was employed to take photographs of high surfaces and inaccessible areas. It enabled safe operation and furnished further data enabling calculation of the size of the photographed defects.

The ranger can be attached directly to the UAV platform (left) without any additional wiring.

The ranger can be attached directly to the UAV platform (left) without any additional wiring.

Everyone involved — pilot, payload operator and observer — used the Ranger application on their own iOS or Android device. An audio warning was set to 3 meters. Whenever the UAV came within this geofence around the silo, audio warning signals were generated, ensuring operational safety.

Camera focus was calibrated at 4 meters. The pilot maneuvered based upon the target audio modus. The target zone was set at 4 meters, with a margin of 50 centimeters. Whenever the pilot was too close or too far, the Ranger respectively indicated “back” or “forward” until the target zone was reached.

The payload operator monitored everything on the visual interface, next to the camera images. When the UAV was in place, pictures were taken at 4 meters. With the extra depth information, and the fixed lens and zoom settings, the actual sizes of the defects could be calculated.

The base station, rover, and display of distance-from-object on any iOS or Android device.

The base station, rover, and display of distance-from-object on any iOS or Android device.

Man versus Machine. The first flight was performed without the Ranger and with an extra observer, standing at 90 degrees between the UAV and the silo. The observer indicated the distance to the pilot and the payload operator with a two-way radio. The pictures taken were not sharp, but unclear and unusable, since they had been taken from too far away. Because of the lack of situational awareness, the results were insufficient.

For the next flight, the Ranger was installed on the UAV in combination with an extra observer at the same location. It became clear that the distances indicated by the observer during the first flight were off by a couple of meters.

Immediately, the added value of the Ranger became clear.

The last flights were all performed without the observer. The results were more precise, reliable and stable than with the observer.

In February, the European Satellite Navigation Competition awarded a special prize to AiRobot for the most innovative use of high-precision GNSS positioning in its project:“UAV Flight Path Learning through GNSS.”

The Flanders Challenge of the ESNC was sponsored by Septentrio; the prize was an AsteRx-m UAS receiver.

AiRobot uses a form of sense-and- avoid technology to ensure accurate and robust location information when executing waypoint flying. The sensing technology enables the UAV to create a temporary map of its surroundings, ensuring that it will not collide with objects in its path.

Ranger is now commercially available. Next, AiRobot is developing collision avoidance solutions with GNSS technology.