TY - GEN
T1 - PCMPC
T2 - 2021 IEEE International Conference on Robotics and Automation, ICRA 2021
AU - Li, Guanrui
AU - Tunchez, Alex
AU - Loianno, Giuseppe
N1 - Funding Information:
∗These authors contributed equally. The authors are with the New York University, Tandon School of Engineering, Brooklyn, NY 11201, USA. email: {lguanrui, atunchez, loiannog}@nyu.edu. This work was supported by Qualcomm Research, the Technology Innovation Institute, Nokia, NYU Wireless, and the young researchers program ”Rita Levi di Montalcini” 2017 grant PGR17W9W4N.
Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - In this paper, we address the Perception-Constrained Model Predictive Control (PCMPC) and state estimation problems for quadrotors with cable suspended payloads using a single camera and Inertial Measurement Unit (IMU). We design a receding-horizon control strategy for cable suspended payloads directly formulated on the system manifold configuration space SE(3)×S2. The approach considers the system dynamics, actuator limits and the camera's Field Of View (FOV) constraint to guarantee the payload's visibility during motion. The monocular camera, IMU, and vehicle's motor speeds are combined to provide estimation of the vehicle's states in 3D space, the payload's states, the cable's direction and velocity. The proposed control and state estimation solution runs in real-time at 500 Hz on a small quadrotor equipped with a limited computational unit. The approach is validated through experimental results considering a cable suspended payload trajectory tracking problem at different speeds.
AB - In this paper, we address the Perception-Constrained Model Predictive Control (PCMPC) and state estimation problems for quadrotors with cable suspended payloads using a single camera and Inertial Measurement Unit (IMU). We design a receding-horizon control strategy for cable suspended payloads directly formulated on the system manifold configuration space SE(3)×S2. The approach considers the system dynamics, actuator limits and the camera's Field Of View (FOV) constraint to guarantee the payload's visibility during motion. The monocular camera, IMU, and vehicle's motor speeds are combined to provide estimation of the vehicle's states in 3D space, the payload's states, the cable's direction and velocity. The proposed control and state estimation solution runs in real-time at 500 Hz on a small quadrotor equipped with a limited computational unit. The approach is validated through experimental results considering a cable suspended payload trajectory tracking problem at different speeds.
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U2 - 10.1109/ICRA48506.2021.9561449
DO - 10.1109/ICRA48506.2021.9561449
M3 - Conference contribution
AN - SCOPUS:85124110646
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 2012
EP - 2018
BT - 2021 IEEE International Conference on Robotics and Automation, ICRA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 30 May 2021 through 5 June 2021
ER -