Objective
One of the major driving forces for the depth perception market is the increasing use of mobile robots and drones for multiple applications. Without reliable vision and particularly depth perception unmanned vehicles are unable to detect obstacles and adaptively plan motion paths. Moreover, the new generation of robotic machines strongly depend on the ability to acquire, organize, and interpret surrounding visual data in real-time in order to stay aware of the environmental situation and act adequately.
Robot and autonomous vehicle manufacturers or system manufacturers do not have the necessary skills, knowledge and know-how for computer vision development, therefore they would much rather use a standard computer vision solution. Currently in the market there is no truly affordable standardized stand-alone COTS 3D computer vision solution, which is capable of high resolution low power long range real-time optical depth sense with deep learning based natural object perception capabilities out of box – something, that is universally appreciated by many mobile robotic system manufacturers and integrators.
Rubedo Sistemos has already developed and successfully tested a prototype of CVM (computer vision module) – the first affordable, compact low power long-range high-resolution real-time depth sense technology for 3D perception at longer distances for mobile robotics. Rubedo CVM has been designed as a maintenance-free standalone product which provides high definition images, accurate measure of the environment depth, and can be trained to extract natural objects of interest in real-time.
Thorough analysis of market and user needs as well as an elaboration of a business plan is needed in order to ensure successful commercialization of Rubedo CVM. This feasibility study will help validating the market in addition to providing a stepping-stone for future preparation of investor readiness as well as serve as a roadmap for market replication of the product.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology mechanical engineering vehicle engineering automotive engineering autonomous vehicles
- social sciences economics and business business and management business models
- natural sciences computer and information sciences artificial intelligence computer vision object detection
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics autonomous robots drones
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
MAIN PROGRAMME
See all projects funded under this programme -
H2020-EU.2.3.1. - Mainstreaming SME support, especially through a dedicated instrument
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-1 - SME instrument phase 1
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-SMEInst-2016-2017
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
51423 KAUNAS
Lithuania
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.