133 citations · 654 across the 31 of their papers we have counts for
10 papers · 1 filter
Nonlinear Model Identification and Observer Design for Thrust Estimation of Small-scale Turbojet Engines
Affaf Junaid Ahamad Momin, Gabriele Nava, Giuseppe LErario +5
Jet-powered vertical takeoff and landing (VTOL) drones require precise thrust estimation to ensure adequate stability margins and robust maneuvering. Small-scale turbojets have bec…
Centroidal Aerodynamic Modeling and Control of Flying Multibody Robots
Tong Hui, Antonello Paolino, Gabriele Nava +5
This paper presents a modeling and control framework for multibody flying robots subject to non-negligible aerodynamic forces acting on the centroidal dynamics. First, aerodynamic…
Competitors-Aware Stochastic Lap Strategy Optimisation for Race Hybrid Vehicles
Francesco Braghin, Luca Paparusso, Manuel Riani +1
World Endurance Championship (WEC) racing events are characterised by a relevant performance gap among competitors. The fastest vehicles category, consisting in hybrid vehicles, ha…
Extended Object Tracking in Curvilinear Road Coordinates for Autonomous Driving
Pragyan Dahal, Simone Mentasti, Stefano Arrigoni +3
In literature, Extended Object Tracking (EOT) algorithms developed for autonomous driving predominantly provide obstacles state estimation in cartesian coordinates in the Vehicle R…
Control of a Hexapod Robot Considering Terrain Interaction
Marco Zangrandi, Stefano Arrigoni, Francesco Braghin
Bio-inspired walking hexapod robots are a relatively young branch in robotics in both state of the art and applications. Despite their high degree of flexibility and adaptability d…
Design of a prototypical platform for autonomous and connected vehicles
Stefano Arrigoni, Simone Mentasti, Federico Cheli +2
Self-driving technology is expected to revolutionize different sectors and is seen as the natural evolution of road vehicles. In the last years, real-world validation of designed a…
Real-Time Forecasting of Driver-Vehicle Dynamics on 3D Roads: a Deep-Learning Framework Leveraging Bayesian Optimisation
Luca Paparusso, Stefano Melzi, Francesco Braghin
Most state-of-the-art works in trajectory forecasting for automotive target predicting the pose and orientation of the agents in the scene. This represents a particularly useful pr…
MPC path-planner for autonomous driving solved by genetic algorithm technique
Stefano Arrigoni, Francesco Braghin, Federico Cheli
Autonomous vehicle's technology is expected to be disruptive for automotive industry in next years. This paper proposes a novel real-time trajectory planner based on a Nonlinear Mo…
LiDAR point-cloud processing based on projection methods: a comparison
Guidong Yang, Simone Mentasti, Mattia Bersani +3
An accurate and rapid-response perception system is fundamental for autonomous vehicles to operate safely. 3D object detection methods handle point clouds given by LiDAR sensors to…
Learning to drive via Apprenticeship Learning and Deep Reinforcement Learning
Wenhui Huang, Francesco Braghin, Zhuo Wang
With the implementation of reinforcement learning (RL) algorithms, current state-of-art autonomous vehicle technology have the potential to get closer to full automation. However,…