Advances in robust autonomy have increased our ability to adopt robotic systems for exploration of unstructured and uncertain environments. Particularly, successful field tests have demonstrated the tremendous potential of deploying robots for exploration and data collection tasks in extreme environments such as planetary surfaces and ocean trenches. However, various challenges exist, originating from algorithmic limitations, as well as environmental modeling, sensing, mobility, and communication constraints. A relevant selection of robotic systems, methods, and sensing devices can overcome these challenges.
The goal of this workshop is to bring together leading researchers from diverse domains to discuss the following questions.
- What new insights or limitations arise when applying algorithms to real-world data as opposed to benchmark datasets or simulations?
- How can we address the limitations of real-world environments—e.g., noisy or sparse data, non-i.i.d. sampling, etc.?
- What challenges exist at the frontiers of robotic exploration of unstructured and extreme environments?
- How can we tie together the categories of systems, methods, and sensing devices to address relevant scientific questions in such environments?
- How can we deal with the algorithmic challenges from the perspective of planning, learning, and decision-making for long-term autonomy of robots in the field?
Learn more, and participate at https://deepgis.org/rss2020workshop .