Olis Robotics announced a new agreement with iCsys, part of the Envirex Group, for iCsys to lead sales, distribution, and support of Olis Robotics’ machine-learning controllers for remotely operated vehicles (ROVs) that increase precision and safety while decreasing costs for ROV operation in the offshore energy market.
“We’re excited to continue to see rapid adoption of our technology, which provides a major evolutionary leap beyond the 1990’s manual control electronics underpinning current ROV’s,” said Olis Robotics CEO Don Pickering. “The technology we put into play makes operations safer, provides new levels of clarity and control for operators, and can save hundreds of thousands of dollars per mission by eliminating the need for multiple robots.”
The next-generation Olis Master Controller (OMC) is based on iCsys’ innovative hardware design and is equipped with key software features of the Olis Robotics CoreOS software platform. The OMC provides a user-friendly interface to control ROVs in remote and local configurations, which significantly improves task efficiencies and decreases total operating costs. The CoreOS software platform is robot agnostic with the ability to switch control between multiple, different robots and can incorporate future machine perception and machine-learning capabilities being developed by Olis.
“Our team extensively tested this technology via multiple sea trials in raw North Sea environments. Through data collected by our test pilots, we know the innovative software and hardware products significantly improve ROV pilot efficiency with manipulation tasks,” said iCsys spokesperson Vidar Haus. “We’re pleased to see interested ROV operator customers already filling a significant pipeline to harness the value and cost savings of the new OMC.”
Olis Robotics launched sales of the OMC in the third quarter of 2019. Additional capabilities through the Digital Workspace application for the CoreOS are projected to be released in the first quarter of 2020. The new application enables enhanced 3D machine perception to produce a live 3D work environment and supports further machine learning capability integration.