The Aerial Robotics Division develops autonomous multirotor aerial vehicles for a wide range of applications, including agricultural monitoring, urban infrastructure inspection, and wildlife surveillance. A strong emphasis on machine/computer vision, control algorithms, and systems engineering define Aerial Robotics' approach to multirotor innovation.


subsystems OVERVIEW

Primary Subsystems:

  • Airframe (design/construct airframes, mount avionics or camera payloads, airframe maintenance, flight-worthiness, antenna tracking, camera gimbal design, robotic arm tools)

  • Flight Operations (plan mission approaches/test flights, develop safety procedures and checklists, operate ground control station/software, perform flight/ground testing)

  • Payload (design/select communications link, design/select on-board computers and payload, integrate algorithms with hardware)

  • Vision (camera system selection, image processing algorithms/computer vision)

 
 Figure 1: concept of operations for 2016-17 multirotor

Figure 1: concept of operations for 2016-17 multirotor

 


AERIAL VEHICLES

 
UT_Blackhawk_USC.JPG

UT Blackhawk(2017-2018)
USC 2018 @ southport, mb

5 kg take-off mass
O.S. Motors OMA-3825-750 with 13x4.5 APC props
Autopilot board by Pixhawk

Vision payloads:
- Teledyne Dalsa Genie Nano XL Robot Vision Camera
- Runcam Split First-Person-View Camera
- Connex Prosight First-Person-View Camera

Communications:
- 433MHz Flight Controls
- 900 MHz Telemetry
- 5.8 GHz Analog FPV link
- 5.0 GHz Digital FPV link

Additional feature(s):
- Aerodynamic-shaped fuselage for drag reduction
- Carbon-Fibre fuselage for reduced weight

 
UT_Skyhawk_2016_2017.JPG

UT Skyhawk (2016-2017)
USC 2017 @ Alma, QC

5 kg take-off mass
O.S. Motors OMA-3825-750 with 13x4.5 APC props
Autopilot board by Pixhawk
Nvidia Jetson TX1 on-board computer

Vision payloads:
- Leopard Imaging IMX274 4K Camera
- Garmin Virb 30 Action Camera

Communications:
- 2.4 GHz flight controls
- 900 MHz telemetry
- 5.8 GHz FPV link

Additional feature(s):
- Aerodynamic-shaped fuselage for drag reduction
- Egg-retrieval mechanism

 
UT_Whirlybird_USC.JPG

UT Whirlybird (2015-2016)
USC 2016 @ Southport, MB

3 kg take-off mass
O.S. Motors OMA-3805-1200 with 11x5.5 APC props
Autopilot board by EMLID Navio+ with Raspberry Pi 2

Vision payloads:
- Teledyne Dalsa Genie Nano C1920 with 8mm lens
- GoPro / Yi Action Camera
- Raspi IR Camera

Communications:
- 2.4 GHz flight controls
- 900 MHz telemetry

Additional feature(s):
- Probe deployment servo mechanism


ACHIEVEMENTS AND AWARDS

 
USC_2018_Team.JPG

Unmanned Systems Canada (USC)

2018 SUAS Competition

 

3rd in Phase I Design Report
10th in Phase II Flight Operations

 

 
UTAT_AeRo_USC2017_teampic.JPG

Unmanned Systems Canada (USC)

2017 SUAS Competition

 

1st in Phase I Design Report
4th in Phase II Flight Operations
Judges Award (for Professionalism and Reliability of Flight Operations)

 
 
UTAT_AeRo_USC2016_teampic.JPG

Unmanned Systems Canada (USC)

2017 SUAS Competition

 

2nd in Phase I Design Report
10th in Phase II Flight Operations

 

EXECUTIVE TEAM 2017-2018

Not pictured:
Florence Chan, Chief Engineer
Flight Operations Lead

  Justin Hai  Director of Aerial Robotics

Justin Hai
Director of Aerial Robotics

  Timothy Lock  Vision Lead

Timothy Lock
Vision Lead

  Katrina Cecco  Airframe Lead

Katrina Cecco
Airframe Lead

  Abdul Derh  Advisor

Abdul Derh
Advisor

  Madeline Zhang  Payload Lead

Madeline Zhang
Payload Lead

  YihTang Yeo  Advisor

YihTang Yeo
Advisor

CURRENT MEMBERS 2018-2019

Martin Ffrench
Ken Guo
Esther Ho
Michael Holmes
Sue Kim
Kimberley Lau
Joshua Madero
Saiyam Patel
Jing Yi Xie
Suhayb Bashir Yousif
Melissa Zalewski
Yingzhuo Zhou