This paper presents TOPPQuad, an algorithm that generates time-optimal trajectories for quadrotors while explicitly incorporating their rigid body dynamics and constraints, such as bounds on inputs (including motor thrusts) and state of the vehicle.
Incorporating jerk constraints into time-optimal trajectory planning for industrial manipulators can enhance energy efficiency, durability, and safety through smoother motion profiles.
A path-following model predictive control (MPC) formulation is proposed to enable efficient and safe human-robot handovers by incorporating a Gaussian process-based prediction of the handover location and adapting the error bounds during the handover.