Simulators for Mobile Social Robots:State-of-the-Art and Challenges

TL;DR

This paper reviews current simulation frameworks for mobile social robots, highlighting their limitations and the need for more realistic, flexible 3D pedestrian-rich environments to better test navigation algorithms in human-centric settings.

Contribution

It evaluates existing simulators, identifies key requirements, and discusses the challenges and gaps in current simulation tools for mobile social robots.

Findings

Pedsim_ros and SocNavBench are the most comprehensive existing frameworks.

Current simulators lack realistic pedestrian behavior modeling.

There is a need for more flexible, realistic 3D simulation environments.

Abstract

The future robots are expected to work in a shared physical space with humans [1], however, the presence of humans leads to a dynamic environment that is challenging for mobile robots to navigate. The path planning algorithms designed to navigate a collision free path in complex human environments are often tested in real environments due to the lack of simulation frameworks. This paper identifies key requirements for an ideal simulator for this task, evaluates existing simulation frameworks and most importantly, it identifies the challenges and limitations of the existing simulation techniques. First and foremost, we recognize that the simulators needed for the purpose of testing mobile robots designed for human environments are unique as they must model realistic pedestrian behavior in addition to the modelling of mobile robots. Our study finds that Pedsim_ros [2] and a more recent SocNavBench framework [3] are the only two 3D simulation frameworks that meet most of the key requirements defined in our paper. In summary, we identify the need for developing more simulators that offer an ability to create realistic 3D pedestrian rich virtual environments along with the flexibility of designing complex robots and their sensor models from scratch.