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Online control of quadrotor and camera with MPC for robust vision-based flight
Implement an online MPC for the control of a drone in a indoor environment, using vision based positioning.
Keywords: MPC, Control, Real-time, Drone
In robotic systems that use Visual Odometry for localization, the quality of the position estimate
depends strongly on the camera position and orientation. This is due to the fact that its surroundings define the visual features based on which the position estimate is computed.
In this thesis, you will develop an on-line optimization approach (MPC) to control quadrotor and camera gimbal. Approaches like SLAM build maps from observed visual features which enable the evaluation of the position estimate quality for a particular drone position offline. The goal is to leverage such maps to find optimal quadrotor/camera trajectory when moving quadrotor from point to point. Your task is to come up with MPC-based approach to solve this task efficiently in real-time.
The thesis is done in collaboration with Tinamu Labs, a young and dynamic startup with the focus of
bringing robotic technology into the real world. You will have the opportunity to test your algorithm
with Tinamu’s robotic system and collaborate with their engineers.
**Tasks:**
In particular, the student will:
- Review literature on trajectory optimization and path planning algorithms used in Robotics with
- a focus on MPC methods for quadrotors.
- Create a real-time optimization approach for the given task. The focus is to make
- computationally tractable approach that can run on on-board computer.
- Verify the concept in a simulation environment.
- Test and evaluate the algorithm in the real-world.
-
**Requirements:**
We are looking for an independent student who:
- Is motivated to work with a real-world robotic system.
- Has basic knowledge in MPC.
- Has background knowledge in Systems Control.
- Has experience with Python or MATLAB (C++ is a plus).
In robotic systems that use Visual Odometry for localization, the quality of the position estimate depends strongly on the camera position and orientation. This is due to the fact that its surroundings define the visual features based on which the position estimate is computed.
In this thesis, you will develop an on-line optimization approach (MPC) to control quadrotor and camera gimbal. Approaches like SLAM build maps from observed visual features which enable the evaluation of the position estimate quality for a particular drone position offline. The goal is to leverage such maps to find optimal quadrotor/camera trajectory when moving quadrotor from point to point. Your task is to come up with MPC-based approach to solve this task efficiently in real-time.
The thesis is done in collaboration with Tinamu Labs, a young and dynamic startup with the focus of bringing robotic technology into the real world. You will have the opportunity to test your algorithm with Tinamu’s robotic system and collaborate with their engineers.
**Tasks:**
In particular, the student will:
- Review literature on trajectory optimization and path planning algorithms used in Robotics with - a focus on MPC methods for quadrotors. - Create a real-time optimization approach for the given task. The focus is to make - computationally tractable approach that can run on on-board computer. - Verify the concept in a simulation environment. - Test and evaluate the algorithm in the real-world. - **Requirements:**
We are looking for an independent student who: - Is motivated to work with a real-world robotic system. - Has basic knowledge in MPC. - Has background knowledge in Systems Control. - Has experience with Python or MATLAB (C++ is a plus).
Not specified
Does this topic sound interesting to you? Please contact us!
balula@control.ee.ethz.ch
dliaomc@control.ee.ethz.ch
christoph@tinamu-labs.com
stefan@tinamu-labs.com
Does this topic sound interesting to you? Please contact us!