A Multifidelity Sim-to-Real Pipeline for Verifiable and Compositional Reinforcement Learning

no code implementations • 2 Dec 2023 • Cyrus Neary, Christian Ellis, Aryaman Singh Samyal, Craig Lennon, Ufuk Topcu

We propose and demonstrate a compositional framework for training and verifying reinforcement learning (RL) systems within a multifidelity sim-to-real pipeline, in order to deploy reliable and adaptable RL policies on physical hardware.

reinforcement-learning Reinforcement Learning (RL)

Verifiable Reinforcement Learning Systems via Compositionality

no code implementations • 9 Sep 2023 • Cyrus Neary, Aryaman Singh Samyal, Christos Verginis, Murat Cubuktepe, Ufuk Topcu

We propose a framework for verifiable and compositional reinforcement learning (RL) in which a collection of RL subsystems, each of which learns to accomplish a separate subtask, are composed to achieve an overall task.

reinforcement-learning Reinforcement Learning (RL)

Analysis and Adaptation of YOLOv4 for Object Detection in Aerial Images

no code implementations • 18 Mar 2022 • Aryaman Singh Samyal, Akshatha K R, Soham Hans, Karunakar A K, Satish Shenoy B

The recent and rapid growth in Unmanned Aerial Vehicles (UAVs) deployment for various computer vision tasks has paved the path for numerous opportunities to make them more effective and valuable.

Object object-detection +2