Seminario: Optimal Motion Planning for Multiple UAV Missions

Il seminario sarà tenuto da Venanzio Cichella, Department of Mechanical Engineering, University of Iowa, USA.

  • Data: 17 dicembre 2019

  • Luogo: Aula 5.5, Scuola di Ingegneria, viale Risorgimento 2, Bologna

  • Modalità d'accesso: Ingresso libero

Contatto di riferimento:

About the speaker

Venanzio Cichella received his B.S. and M.S. in Automation Engineering in 2007 and 2011, respectively, from the University of Bologna, Italy. He got his Ph.D. in Mechanical Engineering in 2018 from the University of Illinois at Urbana-Champaign, majoring in planning and control of multiple autonomous systems. He is currently an Assistant Professor at the Mechanical Engineering department at the University of Iowa. His research interests include cooperative control of autonomous systems, collision avoidance, optimal control, machine learning, and human-centered autonomous vehicle design.


Advances in technology and network solutions have enabled operations of multiple unmanned aerial vehicles (UAVs), providing increased reliability and cost effectiveness compared to the use of single large vehicles acting alone. To enable safe deployment of groups of UAVs, these vehicles must be capable of performing missions in a cooperative fashion to achieve common objectives. During these missions, the vehicles must be able to operate safely and execute coordinated tasks in complex, highly uncertain environments while maneuvering in close proximity to each other and to obstacles. This poses multiple challenges inherent to the design, development, and operation of multiple UAVs. Motivated by these ideas, the first part of this talk will introduce and discuss some challenges for the safe operation of multiple UAVs missions in real-world environments. I will focus in particular on the problem of enabling multiple vehicles to perform desired missions in cooperative ways. I will proceed by presenting methodologies aimed at addressing these challenges, with emphasis on our work on real-time optimal motion planning.