Safety-aware Control
Safety-Aware Control is a control methodology in human-robot interaction that, as a refinement of general robotic control strategies, explicitly integrates real-time safety considerations—such as collision avoidance, risk assessment, and human intent prediction—into the control loop to proactively ensure physical and psychological safety during dynamic interactions.
155
Publications
8.2K
Citations
478
Authors
171
Institutions
Publications per year
2017–2026
93
155
Learning-Based Model Predictive Control for Safe Exploration
Torsten Koller, Felix Berkenkamp, Matteo Turchetta et al. · 2018 · 318 citations
1–5 of 155
478
6
h-index
6
h-index
5
h-index
5
h-index
4
h-index
1–5 of 478
171
Technical University of Munich
Munich, Germany
12 h-index
36 publications
2.1K citations
Politecnico di Milano
Milan, Italy
8 h-index
21 publications
634 citations
University of California, Berkeley
Berkeley, United States
7 h-index
18 publications
538 citations
ETH Zurich
Zurich, Switzerland
6 h-index
11 publications
1.8K citations
California Institute of Technology
Pasadena, United States
5 h-index
16 publications
578 citations
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Cologne, Germany
4 h-index
16 publications
1.6K citations
Piaggio (Italy)
Pontedera, Italy
4 h-index
9 publications
1K citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
16 publications
1K citations
1–8 of 171
6 publications · 337 citations
6
h-index
5 publications · 234 citations
5
h-index
Repository · 5 publications · 366 citations
5
h-index
4 publications · 219 citations
4
h-index
3 publications · 444 citations
4
h-index
1–5