Open Science Research Excellence

Mario Gianni

Publications

2

Publications

2
10004629
MIOM: A Mixed-Initiative Operational Model for Robots in Urban Search and Rescue
Abstract:
In this paper, we describe a Mixed-Initiative Operational Model (MIOM) which directly intervenes on the state of the functionalities embedded into a robot for Urban Search&Rescue (USAR) domain applications. MIOM extends the reasoning capabilities of the vehicle, i.e. mapping, path planning, visual perception and trajectory tracking, with operator knowledge. Especially in USAR scenarios, this coupled initiative has the main advantage of enhancing the overall performance of a rescue mission. In-field experiments with rescue responders have been carried out to evaluate the effectiveness of this operational model.
Keywords:
Actively articulated tracked vehicles, mixed-initiative planning interfeces, robot planning, urban search and rescue.
1
10004630
Learning the Dynamics of Articulated Tracked Vehicles
Abstract:
In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.
Keywords:
Dirichlet processes, Gaussian processes, robot control learning, tracked vehicles.