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cs.RO2025

DiAReL: Reinforcement Learning with Disturbance Awareness for Robust Sim2Real Policy Transfer in Robot Control

Mohammadhossein Malmir, Josip Josifovski, Noah Klarmann +1

Delayed Markov decision processes (DMDPs) fulfill the Markov property by augmenting the state space of agents with a finite time window of recently committed actions. In reliance o…

cs.RO2025

Safe Continual Domain Adaptation after Sim2Real Transfer of Reinforcement Learning Policies in Robotics

Josip Josifovski, Shangding Gu, Mohammadhossein Malmir +5

Domain randomization has emerged as a fundamental technique in reinforcement learning (RL) to facilitate the transfer of policies from simulation to real-world robotic applications…

cs.RO2024

DexGANGrasp: Dexterous Generative Adversarial Grasping Synthesis for Task-Oriented Manipulation

Qian Feng, David S. Martinez Lema, Mohammadhossein Malmir +4

We introduce DexGanGrasp, a dexterous grasping synthesis method that generates and evaluates grasps with single view in real time. DexGanGrasp comprises a Conditional Generative Ad…

cs.RO2024

Continual Domain Randomization

Josip Josifovski, Sayantan Auddy, Mohammadhossein Malmir +3

Domain Randomization (DR) is commonly used for sim2real transfer of reinforcement learning (RL) policies in robotics. Most DR approaches require a simulator with a fixed set of tun…

cs.RO2024

State Representations as Incentives for Reinforcement Learning Agents: A Sim2Real Analysis on Robotic Grasping

Panagiotis Petropoulakis, Ludwig Gräf, Mohammadhossein Malmir +2

Choosing an appropriate representation of the environment for the underlying decision-making process of the reinforcement learning agent is not always straightforward. The state re…