Problem
Agile flight through clutter requires a dynamically feasible trajectory that respects obstacles, orientation, and higher-order motion limits rather than treating the vehicle as a point moving along a geometric path.
Selected research
SQuAT Plan
Agile quadrotor trajectory planning
Time-optimal, jerk-constrained trajectory generation through cluttered environments with nonlinear optimization and ROS visualization.
- Context
- Course project · UCLA · 2022
- Collaboration
- With Ryan Nemiroff · Instructor: Brett T. Lopez
- Areas
- Trajectory optimization · Quadrotors · ROS
Contribution
The project implements nonlinear trajectory optimization with GEKKO, geometric obstacle constraints, quaternion-based orientation modeling, and both three-dimensional and ROS/RViz visualization.
Aaron John Sabu and Ryan Nemiroff developed the project for UCLA MAE 271D, taught by Brett T. Lopez.
Outcome
The result is a public course-project codebase and technical presentation demonstrating the planning formulation in simulation.
The work was developed and evaluated in simulation as a collaborative course project.
Citation
How to cite this work
Suggested software citation · collaborative course project