UTIAS FSC

Five more to go!!!!✈️✈️✈️✈️✈️

Summer days in FSC 🌻

ROBOTICS AND AUTOMATION SOCIETY

Best Unmanned Aerial Vehicles Paper Award ✨✨🎉🎉🎉🌸🌸👏👏👏👏😊😊🙌🙌🙌🙌🙌🙌

IEEE International Conference on Robotics and Automation - ICRA 2024

Presented to Hugh H.-T. Liu
For the paper co-authored with Chao Qin, Maxime Simon Joseph Michet, and Jingxiang Chen

“Time-Optimal Gate-Traversing Planner for Autonomous Drone Racing”

Congratulations 🎉🎈🎊🍾😊😍👏👏🌸🙌🙌🎉🎉

Dr. Longhao Qian, a postdoctoral fellow at the FSC Lab, presented his work on "Trajectory Control of A Fixed-wing Crop Monitoring Drone: A Case Study" at the CASI/IASC Canadian Aeronautics and Space Institute AERO 2023 Conference in Ottawa. Co-authors include Yi Lok Lo from the Department of Mechanical Engineering at the University of Hong Kong and Professor Hugh Liu, head of the FSC Lab.

Abstract of the Presentation

"Using UAVs to perform automated crop monitoring is essential in the future agricultural industry. To achieve this, planning and control are the two essential components. In this work, a fixed-wing drone is used to perform the crop monitoring mission. A path controller based on the control augmented system (CAS) and the C* control law is proposed as the inner control loop. Based on the inner control loop, straight-line path-following and circular path-following control laws are proposed, forming the complete scan trajectory control family. Simulation shows that under the control of the proposed algorithm, the drone is able to perform the back-and-forth crop scanning mission. In the future, machine learning techniques such as Gaussian processes are going to be used to compensate for wind disturbance."

CASI presentation: https://lnkd.in/gMNtrQeg

Longhao and Kevin 👏👏📚📖📑

Aerospace Birthday vibe!!!🩵🩵🎉✨🥷🪂😂

What is your dream?

🚁Research on Human-Robot Interaction in Autonomous Flight! 🌟

We are excited to share an update on our ongoing project at the FSC Lab. Our Human-Robot Interaction (HRI) team, led by Darya, is delving into the fascinating world of human-robot interaction in autonomous flight. This summer, our enthusiastic and talented summer students, Sana and Harry, have been making remarkable strides in our research! 🙌✨

Our focus is to understand how the trust level and its correlated factors influence the optimal path deviation made by human operators during flight, while considering the collision possibility of the auto-generated path. This captivating area of study aims to uncover the factors shaping these choices. Our mission is to optimize the overall effectiveness by unraveling the underlying reasons behind different behaviors and exploring their variations based on the operator's level of trust. Moreover, we aim to propose new optimal trajectories that take into account the user's trust level, maximizing performance, efficiency, and safety simultaneously.

Sana and Harry have been developing innovative measurement tools that are indispensable for data analysis. As we approach the upcoming data collection phase, we anticipate that these tools will provide deeper insights into the distinct behavior and preferences of operators. Stay tuned for future updates!

Figure: Partial Panel of Selected Data Analysis Tool
The upper panels present the analysis of 15 runs conducted by Participant X. The lower left panel showcases the auto to manual ratio and crash data for 10 randomly selected participants each for 15 runs. The lower right panel illustrates an example of a flown trajectory for one participant, one run.

FSC_Jungle🌳🌳🌳

The greenest office at UTIAS 💚💚💚