@article {2021j-BarFraOri,
	title = {Towards Safe Human-Quadrotor Interaction: Mixed-Initiative Control via Real-Time NMPC},
	journal = {IEEE Robotics and Automation Letters, Special Issue on Shared Autonomy for Physical Human-Robot Interaction},
	volume = {6},
	year = {2021},
	pages = {7611-7618},
	abstract = {This paper presents a novel algorithm for blending human inputs and automatic controller commands, guarantee- ing safety in mixed-initiative interactions between humans and quadrotors. The algorithm is based on nonlinear model predictive control (NMPC) and involves using the state solution to assess whether safety- and/or task-related rules are met to mix control authority. The mixing is attained through the convex combination of human and actual robot costs and is driven by a continuous function that measures the rules{\textquoteright} violation. To achieve real-time feasibility, we rely on an efficient real-time iteration (RTI) variant of a sequential quadratic programming (SQP) scheme to cast the mixed-initiative controller. We demonstrate the effectiveness of our algorithm through numerical simulations, where a second autonomous algorithm is used to emulate the behavior of pilots with different skill levels. Simulations show that our scheme provides suitable assistance to pilots, especially novices, in a workspace with obstacles while underpinning computational efficiency.},
	doi = {10.1109/LRA.2021.3096502},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2021j-BarFraOri.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2021j-BarFraOri.mp4},
	author = {Barbara Barros Carlos and Antonio Franchi and Giuseppe Oriolo}
}
