Reference number : GC-2017-Q2-00012, amendment number : , agreement type : G, recipient legal name : Chen, Xiang (University of Windsor), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Grants for Universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Autonomous vehicles such as Unmanned Aerial Vehicle (UAV) are gaining increasing acceptance in various_x000D_
applications. The UAV industry will see explosive growth in terms of both quantities and the areas of_x000D_
applications while the autonomous or semi-autonomous vehicles will be in the market in foreseeable future. It_x000D_
is observed that the trend of autopilot control is going towards intelligent as autonomous or semi-autonomous_x000D_
operations of UAVs become more and more popular and necessary. Therefore, how to develop distributed_x000D_
sensors or sensor network based intelligent autopilot controllers is of vital interest and also technology-wise_x000D_
innovative for the UAV industry. In this regard, a network of field sensors such as cameras, sonic sensor,_x000D_
RADAR, LiDAR, etc., has to be applied with information fused together to provide the perception of the_x000D_
surrounding environment. The autopilot controller could then make decision based on the fused information to_x000D_
maneuver the autonomous operation of UAVs._x000D_
In this project, it is intended to 1. develop distributed 3-D reconstruction algorithms for sensing and perception_x000D_
performed by cameras and LiDARs; 2. develop sensing data fusion mechanism in a networked environment to_x000D_
be integrated with the flight autopilot control; and 3. implement the controller with advanced hardware_x000D_
technology such as multi-processors with graphic processing unit (GPU) or FPGA solution upon cost and_x000D_
efficiency assessment. In particular, the distributed algorithms will be developed for field sensor nodes and the_x000D_
data fusion mechanism will be explored and developed for a networked and complimentary configuration of_x000D_
field sensors in order to assemble the information collected by each individual sensor in an automated way._x000D_
Based on this distributed structure and the data fusion mechanism, the intelligent autopilot controller will be_x000D_
built up for autonomous operation of UAVs. It is expected that the project deliverable be applied to optimize_x000D_
intelligent autopilot design for various autonomous missions., program purpose french : Autonomous vehicles such as Unmanned Aerial Vehicle (UAV) are gaining increasing acceptance in various_x000D_
applications. The UAV industry will see explosive growth in terms of both quantities and the areas of_x000D_
applications while the autonomous or semi-autonomous vehicles will be in the market in foreseeable future. It_x000D_
is observed that the trend of autopilot control is going towards intelligent as autonomous or semi-autonomous_x000D_
operations of UAVs become more and more popular and necessary. Therefore, how to develop distributed_x000D_
sensors or sensor network based intelligent autopilot controllers is of vital interest and also technology-wise_x000D_
innovative for the UAV industry. In this regard, a network of field sensors such as cameras, sonic sensor,_x000D_
RADAR, LiDAR, etc., has to be applied with information fused together to provide the perception of the_x000D_
surrounding environment. The autopilot controller could then make decision based on the fused information to_x000D_
maneuver the autonomous operation of UAVs._x000D_
In this project, it is intended to 1. develop distributed 3-D reconstruction algorithms for sensing and perception_x000D_
performed by cameras and LiDARs; 2. develop sensing data fusion mechanism in a networked environment to_x000D_
be integrated with the flight autopilot control; and 3. implement the controller with advanced hardware_x000D_
technology such as multi-processors with graphic processing unit (GPU) or FPGA solution upon cost and_x000D_
efficiency assessment. In particular, the distributed algorithms will be developed for field sensor nodes and the_x000D_
data fusion mechanism will be explored and developed for a networked and complimentary configuration of_x000D_
field sensors in order to assemble the information collected by each individual sensor in an automated way._x000D_
Based on this distributed structure and the data fusion mechanism, the intelligent autopilot controller will be_x000D_
built up for autonomous operation of UAVs. It is expected that the project deliverable be applied to optimize_x000D_
intelligent autopilot design for various autonomous missions., agreement title english : Distributed Autonomous Pilot Control for Unmanned Aerial Vehicles (UAVs), agreement title french : Distributed Autonomous Pilot Control for Unmanned Aerial Vehicles (UAVs), agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-07-12, 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 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., 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