Reference number : GC-2017-Q1-03480, amendment number : , agreement type : G, recipient legal name : Najjaran, Homayoun (The University of British Columbia), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : The outcome of research in the global robotics and mechatronics community over the past two decades has revolutionized both the aerospace and automotive industries by providing the technologies used in unmanned aerial vehicles (UAVs) and self-driving cars. A number of automotive and aerospace manufacturers, as well as high-tech companies, have made substantial investments in their research and development programs to introduce the first flawless and fully autonomous vehicle technology and to gain a greater share of the market. However, the fate of these investments is linked to acceptance and adoption of autonomous technology by regulators and the public . The proposed research program focuses on improving the robustness of autonomous vehicle technology for safer and more reliable UAVs and self-driving cars. This goal will be achieved by investigating every component of the autonomous navigation process with specific emphasis on the following three aspects. 
First, innovative machine learning methods based on convolutional neural network deep learning will be developed and used to enable more efficient object detection in unknown and complex environments. In this way, a direct perception approach for robust autonomous navigation of UAVs and AVs is introduced. 
Second, approximate reasoning methods for intelligent high-level decision making will be developed to provide a systematic way of responding to vague states and contradictory evidence in unforeseen driving or flight scenarios. A versatile inference engine will be developed by incorporating network-based machine learning, fuzzy logic and evidential reasoning methods. 
Third, a stable hybrid control system will be developed that can provide fast deceleration and swerving of AVs, and high-pitch maneuvers. Using this hybrid control scheme, a proof-of-concept active fault tolerant control (AFTC) system will be developed for a quadrotor UAV. 
The contributions of the proposed research will be creating the potential for: i) a prototype autonomous car that is safe to operate on public roads, and ii) a commercial-grade UAV safe to fly beyond line of sight. The proposed research will contribute to the concurrent global research aiming to resolve the dilemma of AV technology by introducing innovative human-like approximate reasoning paradigms that accounts for moral, social and legal standards. In conclusion, independent, factual and transparent research originating from academia will influence the public acceptance and adoption of AV technology., program purpose french : The outcome of research in the global robotics and mechatronics community over the past two decades has revolutionized both the aerospace and automotive industries by providing the technologies used in unmanned aerial vehicles (UAVs) and self-driving cars. A number of automotive and aerospace manufacturers, as well as high-tech companies, have made substantial investments in their research and development programs to introduce the first flawless and fully autonomous vehicle technology and to gain a greater share of the market. However, the fate of these investments is linked to acceptance and adoption of autonomous technology by regulators and the public . The proposed research program focuses on improving the robustness of autonomous vehicle technology for safer and more reliable UAVs and self-driving cars. This goal will be achieved by investigating every component of the autonomous navigation process with specific emphasis on the following three aspects. 
First, innovative machine learning methods based on convolutional neural network deep learning will be developed and used to enable more efficient object detection in unknown and complex environments. In this way, a direct perception approach for robust autonomous navigation of UAVs and AVs is introduced. 
Second, approximate reasoning methods for intelligent high-level decision making will be developed to provide a systematic way of responding to vague states and contradictory evidence in unforeseen driving or flight scenarios. A versatile inference engine will be developed by incorporating network-based machine learning, fuzzy logic and evidential reasoning methods. 
Third, a stable hybrid control system will be developed that can provide fast deceleration and swerving of AVs, and high-pitch maneuvers. Using this hybrid control scheme, a proof-of-concept active fault tolerant control (AFTC) system will be developed for a quadrotor UAV. 
The contributions of the proposed research will be creating the potential for: i) a prototype autonomous car that is safe to operate on public roads, and ii) a commercial-grade UAV safe to fly beyond line of sight. The proposed research will contribute to the concurrent global research aiming to resolve the dilemma of AV technology by introducing innovative human-like approximate reasoning paradigms that accounts for moral, social and legal standards. In conclusion, independent, factual and transparent research originating from academia will influence the public acceptance and adoption of AV technology., agreement title english : Safe and Robust Autonomous Vehicle Technology, agreement title french : Safe and Robust Autonomous Vehicle Technology, agreement number : RGPIN, agreement value : 155000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada