Amr Alanwar — accepted AI-conference papers

2022

Enhancing Data-Driven Reachability Analysis using Temporal Logic Side Information

Amr Alanwar, Frank J. Jiang, Maryam Sharifi, Dimos V. Dimarogonas, Karl H. Johansson

ICRA 2022poster

This paper presents algorithms for performing data-driven reachability analysis under temporal logic side information. In certain scenarios, the data-driven reachable sets of a robot can be prohibitively conservative due to the inherent noise in the robot's historical measurement data. In the same s…

Cited by 7 Source ↗Scholar ↗

2022

Safe Reinforcement Learning Using Black-Box Reachability Analysis

Mahmoud Selim, Amr Alanwar, Shreyas Kousik, Grace Xingxin Gao, Marco Pavone, Karl Henrik Johansson

RA-L 2022

Reinforcement learning (RL) is capable of sophisticated motion planning and control for robots in uncertain environments. However, state-of-the-art deep RL approaches typically lack safety guarantees, especially when the robot and environment models are unknown. To justify widespread deployment, rob

Cited by 42 Source ↗code ↗Scholar ↗