5 papers
Context Representation via Action-Free Transformer encoder-decoder for Meta Reinforcement Learning
Amir M. Soufi Enayati, Homayoun Honari, Homayoun Najjaran
Reinforcement learning (RL) enables robots to operate in uncertain environments, but standard approaches often struggle with poor generalization to unseen tasks. Context-adaptive m…
A Cross-Environment and Cross-Embodiment Path Planning Framework via a Conditional Diffusion Model
Mehran Ghafarian Tamizi, Homayoun Honari, Amir Mehdi Soufi Enayati +2
Path planning for a robotic system in high-dimensional cluttered environments needs to be efficient, safe, and adaptable for different environments and hardware. Conventional metho…
Visual Deformation Detection Using Soft Material Simulation for Pre-training of Condition Assessment Models
Joel Sol, Amir M. Soufi Enayati, Homayoun Najjaran
This paper addresses the challenge of geometric quality assurance in manufacturing, particularly when human assessment is required. It proposes using Blender, an open-source simula…
Using Implicit Behavior Cloning and Dynamic Movement Primitive to Facilitate Reinforcement Learning for Robot Motion Planning
Zengjie Zhang, Jayden Hong, Amir Soufi Enayati +1
Reinforcement learning (RL) for motion planning of multi-degree-of-freedom robots still suffers from low efficiency in terms of slow training speed and poor generalizability. In th…
Meta SAC-Lag: Towards Deployable Safe Reinforcement Learning via MetaGradient-based Hyperparameter Tuning
Homayoun Honari, Amir Mehdi Soufi Enayati, Mehran Ghafarian Tamizi +1
Safe Reinforcement Learning (Safe RL) is one of the prevalently studied subcategories of trial-and-error-based methods with the intention to be deployed on real-world systems. In s…