The object perception capabilities of humans are impressive, and this becomes even more
evident when trying to develop solutions with a similar proficiency in autonomous robots …

Reproducibility is one of the core dimensions that concur to deliver Trustworthy Artificial
Intelligence. Broadly speaking, reproducibility can be defined as the possibility to reproduce …

Sim2Real transfer has gained popularity because it helps transfer from inexpensive
simulators to real world. This paper presents a novel system that fuses components in a …

The simulation-to-reality (sim2real) problem is a common issue when deploying simulation-
trained models to real-world scenarios, especially given the extremely high imbalance …

Tactile sensing presents a promising opportunity for enhancing the interaction capabilities of
today's robots. BioTac is a commonly used tactile sensor that enables robots to perceive and …

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 …

Choosing an appropriate representation of the environment for the underlying decision-
making process of the\gls {RL} agent is not always straightforward. The state representation …

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