Combined efforts in the fields of neuroscience, computer science, and biology allowed to
design biologically realistic models of the brain based on spiking neural networks. For a …

This letter compares the performance of four different, popular simulation environments for
robotics and reinforcement learning (RL) through a series of benchmarks. The benchmarked …

Object transportation could be a challenging problem for a single robot due to the oversize
and/or overweight issues. A multi-robot system can take the advantage of increased driving …

Current reinforcement learning (RL) methods use simulation models as simple black-box
oracles. In this paper, with the goal of improving the performance exhibited by RL …

This paper presents the software tool used at the Institute of Industrial and Control
Engineering (IOC-UPC) for teaching and research in robot motion planning. The tool allows …

The primary goal of this research is to develop a deep learning-powered robotic solution to
address labor shortages and optimize harvesting processes in strawberry greenhouse …

Advances in hardware design have made wheeled mobile robots (WMRs) exceptionally
mobile. To fully exploit this mobility, we present a novel dynamic model formulation for use in …

This paper presents a novel technique that allows for both computationally fast and
sufficiently plausible simulation of vehicles with non-deformable tracks. The method is based …

Developing control methods that allow legged robots to move with skill and agility remains
one of the grand challenges in robotics. In order to achieve this ambitious goal, legged …

This paper reports on the adaptation of a Lattice Boltzmann based free surface flow solver to
the simulation of complex fluid-ship-ice interactions in marine engineering. The analysis is …