Robotic exploration is a fundamental problem in mobile robotics that addresses one of the most challenging application scenarios to provide an efficient approach to collect information about an unknown environment. There are many motivational scenarios for practical deployment of mobile robots and probably even more approaches promising benefits from deploying several mobile robots. However, what are the real performance guarantees of the modern sophisticated exploration strategies? Do the novel methods and experimental demonstrations provide qualitatively better results in a new principle way or are these improvements only the results of a better tuning for the particular platforms and scenarios? What is the bridge between algorithmic complexity and robotic limitations? How to define scalable solutions?
The goal of the workshop is to foster a discussion about approaches and paradigms studied in artificial intelligence (AI) and multi-agent system (MAS) communities with the robotic limitations and requirements arising from their practical deployment in multi-robot exploration. In particular, the workshop is intended to explore the aforementioned questions within the context of the following scientific challenges:
- How balancing algorithmic (MAS) complexity and robotics limitation?
- How to measure performance in multi-robot exploration?
- How to facilitate the robotic deployment of AI strategies?
- What are the robotic limitations needed to be considered in the exploration strategies?
- What are the multi-robot benchmarks allowing qualitative and quantitative comparisons?
- What is the niche of multi-agent coordination mechanisms and capabilities of nowadays multi-robot systems?