Research into Image Processing Technology for Detecting Airborne Objects
First written in FY2018. 5 of 7 entries say "Advanced", first in FY2019. Latest entry: FY2023.
3 other companies' latest entry also says "Advanced".
- FY2023AdvancedAnnual report
「To accelerate the commercialisation of the object-detection technology using optical-wave sensors for the collision-avoidance system developed through the previous year, the company group began building a standard hardware and software environment for implementing the technology. In fiscal 2022, it built the standard environment required for annotating data.」
To commercialise the collision-avoidance system, the company began building a standard hardware and software environment and built an environment for annotation in fiscal 2022. - FY2022AdvancedAnnual report
「In this research, tests using manned aircraft (helicopters) and small unmanned aircraft were conducted in Minamisoma, Fukushima Prefecture, and Toyokawa, Aichi Prefecture. The collision-avoidance system, including the optical-wave sensor developed by the company group, successfully avoided collisions with manned aircraft approaching at a relative speed of 200 km/h and small unmanned aircraft approaching at a relative speed of 100 km/h.」
In airborne-object detection and collision-avoidance research, testing involving manned aircraft approaching at a relative speed of 200 km/h and small unmanned aircraft approaching at a relative speed of 100 km/h was successfully completed, advancing the project to the demonstration stage. - FY2021AdvancedAnnual report
「During the consolidated fiscal year, the company designed and produced an optical-wave sensor that was miniaturised, made lighter and given lower power consumption for installation on small unmanned aircraft. Miniaturisation and weight reduction were achieved by reducing the hardware configuration and reviewing software processing.」
In its airborne-object detection research, the company advanced the hardware design and production of an optical-wave sensor for small unmanned aircraft, achieving miniaturisation, weight reduction and lower power consumption, and successfully capturing images. - FY2020AdvancedAnnual report
「In demonstration testing of the collision-avoidance system, the company successfully avoided a threat aircraft based on the detection and identification results output by the optical-wave sensor.」
Under NEDO’s DRESS Project, collision-avoidance flight tests involving an unmanned aircraft and a manned helicopter were conducted in Minamisoma, Fukushima Prefecture, and the company successfully avoided the threat aircraft. - FY2020-Q1RestatedAnnual report
「Total research and development expenses for the corporate group during the 3-month period ended 30 June were ¥61 million. There was no material change in the status of the corporate group's research and development activities during the 3-month period ended 30 June.」
No material changes were disclosed regarding research and development activities, including airborne-object detection, and total research and development expenses amounted to ¥61 million. - FY2019AdvancedAnnual report
「During the consolidated fiscal year, in preparation for demonstration testing, the company completed the hardware design and production of each optical-wave sensor unit. With the units mounted on an unmanned helicopter, it confirmed that vibration-isolation performance matched to the aircraft’s vibration characteristics eliminated factors such as blur that affect image processing and maintained image quality. Flight tests were also conducted with the optical-wave sensor units mounted on the unmanned helicopter, and the detection and identification performance for each target object was confirmed under conditions involving close approaches by a manned helicopter and a drone (simulated collision conditions).」
Under NEDO’s DRESS Project, the company progressed through the design and production of optical-wave sensors, their installation on an unmanned helicopter and flight testing, confirming the feasibility of detecting and identifying target objects. - FY2018First statedAnnual report
「The company group was selected as a development manufacturer for NEDO’s “Project for the Realisation of an Energy-Saving Society in which Robots and Drones Play an Active Role” (DRESS Project).」
Under NEDO’s DRESS Project, the company researched the detection and identification of airborne objects using visible-light cameras. The objectives were long-range detection, high-speed processing, lower power consumption and reduced weight, and the feasibility of identifying target distances was confirmed through simulations using moving images of manned and unmanned helicopters and drones.