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Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach
- Source :
- BASE-Bielefeld Academic Search Engine
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- In this work, we present an optimization-based trajectory tracking solution for multirotor aerial robots given a geometrically feasible path. A trajectory planner generates a minimum-time kinematically and dynamically feasible trajectory that includes not only standard restrictions such as continuity and limits on the trajectory, constraints in the waypoints, and maximum distance between the planned trajectory and the given path, but also restrictions in the actuators of the aerial robot based on its dynamic model, guaranteeing that the planned trajectory is achievable. Our novel compact multi-phase trajectory definition, as a set of two different kinds of polynomials, provides a higher semantic encoding of the trajectory, which allows calculating an optimal solution but following a predefined simple profile. A Model Predictive Controller ensures that the planned trajectory is tracked by the aerial robot with the smallest deviation. Its novel formulation takes as inputs all the magnitudes of the planned trajectory (i.e. position and heading, velocity, and acceleration) to generate the control commands, demonstrating through in-lab real flights an improvement of the tracking performance when compared with a controller that only uses the planned position and heading. To support our optimization-based solution, we discuss the most commonly used representations of orientations, as well as both the difference as well as the scalar error between two rotations, in both tridimensional and bidimensional spaces $SO(3)$ and $SO(2)$. We demonstrate that quaternions and error-quaternions have some advantages when compared to other formulations.
- Subjects :
- Optimization
0209 industrial biotechnology
Computer science
UAV
Scalar (mathematics)
Trajectory planning
02 engineering and technology
Remotely operated underwater vehicle
Industrial and Manufacturing Engineering
Computer Science::Robotics
020901 industrial engineering & automation
Artificial Intelligence
Control theory
Mobile robots
Multirotor
Model predictive control
Electrical and Electronic Engineering
Quaternion
Computer science [C05] [Engineering, computing & technology]
Mechanical Engineering
Mobile robot
Sciences informatiques [C05] [Ingénierie, informatique & technologie]
Remotely operated vehicles
Trajectory tracking
Aerial robotics
Control and Systems Engineering
Robot
Actuator
MAV
Software
Subjects
Details
- ISSN :
- 15730409 and 09210296
- Volume :
- 100
- Database :
- OpenAIRE
- Journal :
- Journal of Intelligent & Robotic Systems
- Accession number :
- edsair.doi.dedup.....4a21117dda6205ae3eea2c05200fecd5