Comprehensive Assessment of Orbital Robotics, Space Application Simulation/Machine Learning, and Methods of Hardware in the Loop Validation

Peterson, Marco; Du, Minzhen; Springle, Bryant; Black, Jonathan

doi:10.1109/aero53065.2022.9843216

Cited by 1 publication

(1 citation statement)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The recent wide adoption of deep learning [11,12] and the increased use of industry-standard robotic software [13][14][15] are slowly making their way into space-related applications. Moreover, space applications often use dedicated and heterogeneous computational resources, which creates the need for hardware-in-the-loop (HIL) simulation, allowing the testing of the complex interplay of hardware and software under possibly realistic conditions [16].…”

Section: Introductionmentioning

confidence: 99%

LunarSim: Lunar Rover Simulator Focused on High Visual Fidelity and ROS 2 Integration for Advanced Computer Vision Algorithm Development

Pieczyński,

Ptak,

Kraft

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

Autonomous lunar exploration is a complex task that requires the development of sophisticated algorithms to control the movement of lunar rovers in a challenging environment, based on visual feedback. To train and evaluate these algorithms, it is crucial to have access to both a simulation framework and data that accurately represent the conditions on the lunar surface, with the main focus on providing the visual fidelity necessary for computer vision algorithm development. In this paper, we present a lunar-orientated robotic simulation environment, developed using the Unity game engine, built on top of robot operating system 2 (ROS 2), which enables researchers to generate quality synthetic vision data and test their algorithms for autonomous perception and navigation of lunar rovers in a controlled environment. To demonstrate the versatility of the simulator, we present several use cases in which it is deployed on various efficient hardware platforms, including FPGA and Edge AI devices, to evaluate the performance of different vision-based algorithms for lunar exploration. In general, the simulation environment provides a valuable tool for researchers developing lunar rover systems.

show abstract