TOPPQuad: Dynamically-Feasible Time Optimal Path Parametrization for Quadrotors

TL;DR

TOPPQuad is a novel algorithm that computes time-optimal, dynamically feasible trajectories for quadrotors in cluttered environments, explicitly considering vehicle dynamics and hardware constraints to improve speed and safety.

Contribution

The paper introduces TOPPQuad, a new method for time-optimal path parametrization that guarantees dynamic feasibility and incorporates quadrotor-specific constraints, outperforming previous approaches.

Findings

Generates faster trajectories respecting hardware constraints.

Explicitly incorporates quadrotor dynamics and constraints.

Enables planning for quadrotors with bidirectional motors.

Abstract

Planning time-optimal trajectories for quadrotors in cluttered environments is a challenging, non-convex problem. This paper addresses minimizing the traversal time of a given collision-free geometric path without violating bounds on individual motor thrusts of the vehicle. Previous approaches have either relied on convex relaxations that do not guarantee dynamic feasibility, or have generated overly conservative time parametrizations. We propose TOPPQuad, a time-optimal path parameterization algorithm for quadrotors which explicitly incorporates quadrotor rigid body dynamics and constraints such as bounds on inputs (including motor speeds) and state of the vehicle (including the pose, linear and angular velocity and acceleration). We demonstrate the ability of the planner to generate faster trajectories that respect hardware constraints of the robot compared to several planners with relaxed notions of dynamic feasibility. We also demonstrate how TOPPQuad can be used to plan trajectories for quadrotors that utilize bidirectional motors. Overall, the proposed approach paves a way towards maximizing the efficacy of autonomous micro aerial vehicles while ensuring their safety.