The aim of RELIABLE is to develop control system methodological tools and algorithms that explicitly integrates in the formulation safety constraints and that are provably (mathematically) safe certified. A particular goal is to combine data driven approaches and machine learning techniques (known to be non-reliable, and/or extremely difficult to obtain formal guarantees) with recent optimization control based techniques capable of enforcing invariance in the context of control barrier functions (CBFs) and Control Lyapunov Functions (CLFs) in the presence of challenging restrictions and uncertainties. Another goal is to move from a single system to (possible large scale) safety critical networked systems involving multiple agents operating autonomously over networks in dynamic environments, where additional challenges arise due to the presence of a communication network.
The methodologies will be demonstrated in the following case studies:
- Robotic vehicles in space, aerial and underwater scenarios: remote monitoring and exploration applications;
- Mobile robotics in industry 4.0 scenarios: perception algorithms, reactive planning, navigation and control systems to enable mobile robots to operate autonomously in unstructured environments with effective human-robot collaboration with safety guarantees.
RELIABLE target the following indicators:
Books: 1
Papers in international journals: 12
Communications in international meetings: 21
Communications in national meetings: 5
Organization of seminars and conferences: 3
PhD theses: 3
Master theses: 5
Software: 5
The dissemination of the activities will target several audiences:
1. International (and national) scientific community, through reputed high quality journal publications (IEEE Trans. on Automatic Control, IFAC Automatica, IEEE Trans. on Robotics), and international conferences (CDC, ACC, ICRA, IROS) as well as the organization and participation in dedicated workshops.
2. Students, through actions like seminars, special lectures or experimental demos, summer schools, workshops, and advance training (Master and Doctoral level).
3. Institutional stakeholders from industry and decision makers
4. Public at large. |
