We propose a trajectory-based framework for agile and robust manipulation of cable-suspended loads using multiple quadrotors.
A fully decentralized algorithm enabling multiple UAVs to collaboratively manipulate a cable-suspended load using multi-agent reinforcement learning.
We have addressed the long-standing challenge of controlling and exchanging tools between two multirotor UAVs operating in close vertical proximity.
Meta Adaptive Control for Aerial Manipulators.
We study the performance of using nonlinear MPC on quadrotor fail-safe problem. The result is amazing.
We systematically compare two state-of-the-art flight controllers for quadcopter agile flights, nonlinear MPC and differential-flatness-based controller.
This work proposes a novel control methods for quadcopter agile flights using model-predictive-contouring control.
We propose L1-MPC, an adaptive-model-predictive control framework showing impressive performance against model uncertainties and disturbances.
We introduce a flight controller that can recover a quadrotor with one rotor complete off from arbitrary initial orientations and body rates.