The workshop will be held in conjunction with the 20th Conference of the Italian Association for Artificial Intelligence (AI*IA 2021), the 30 of November 2021
14:00 – Introduction
14:05 – Sessione 1: Collaborative and Social Robotics
| 14:10 | Towards an ontological core for cognitively justified robots Stefano Borgo, Roberta Ferrario, Claudio Masolo and Daniele Porello |
| 14:25 | The role of intelligent telepresence robots for continuously caring elderly people at home Gloria Beraldo, Riccardo De Benedictis, Rami Reddy Devaram, Amedeo Cesta and Gabriella Cortellessa |
| 14:40 | Trust Metrics for Task Assignment in Cooperative Teams of Robots Alberto Grillo, Carmine Recchiuto, Stefano Carpin and Antonio Sgorbissa |
| 14:55 | Cloud Services for Social Robots and Artificial Agents Lucrezia Grassi, Carmine Recchiuto and Antonio Sgorbissa |
| 15:10 | A GAN-based Approach for Generating Culture-Aware Co-Speech Gestures Ariel Gjaci, Carmine Recchiuto and Antonio Sgorbissa |
15:25 – Break
15:30 – Session 2: Robot Planning and Learning
| 15:35 | Multi-robot Sanitization of Railway Stations Based on Deep Q-Learning Riccardo Caccavale, Vincenzo Calà, Mirko Ermini, Alberto Finzi, Vincenzo Lippiello and Fabrizio Tavano |
| 15:50 | A first approach to AGI-based Robot Task Planning Michele Thiella, Elisa Tosello and Enrico Pagello |
| 16:05 | Exploiting Different Levels of Abstractions for Sample Efficient Reinforcement Learning Roberto Cipollone, Giuseppe De Giacomo, Marco Favorito, Luca Iocchi and Fabio Patrizi |
| 16:20 | Learning environment properties in Partially Observable Monte Carlo Planning Maddalena Zuccotto, Alberto Castellini, Marco Piccinelli, Enrico Marchesini and Alessandro Farinelli |
16:35 – Break
16:40 – Session 3: Mobile Robotics
| 16:45 | Predicting Performance of SLAM Algorithms Matteo Luperto, Valerio Castelli, Fabio Bonsignorio and Francesco Amigoni |
| 17:00 | People-aware navigation: AI-driven approaches to enhance the robot’s navigation capabilities Gloria Beraldo, Alberto Bacchin and Emanuele Menegatti |
17:15 – Session 4: Keynote
| 17:15 | Safe Reinforcement Learning for Intelligent Robotic Systems Alessandro Farinelli |
| Intelligent Robotic Systems are a critical asset in several application scenarios, ranging from agile manufacturing, to environmental monitoring and logistics. A crucial element for Intelligent Robotic Systems to be successfully deployed in such scenarios is the ability to adapt their behaviours to changes in the operational environments, and Reinforcement Learning is a widely used approach to achieve this. In the last years, Reinforcement Learning (and Deep RL) achieved ground-breaking successes in several scenarios (e.g., Games and Video-Games). However, the adoption of RL techniques for robotics is still challenging. In this talk we will consider two key aspects related to RL for Intelligent Robotic Systems. Specifically, we will focus on formal verification approaches for Deep RL, describing a novel approach (i.e., ProVe) that is based on interval algebra and that is designed to verify behavioural properties of a DRL agent Moreover, we will present an approach for identifying and shielding unexpected decisions in Partially Observable Monte-Carlo Planning. This approach is based on Satisfiability Modulo Theory (SMT) and is designed to analyse POMCP policies by inspecting their traces. For both aspects we will present recent results, current challenges and future directions, highlighting application scenarios where these techniques can have a key impact. |