RSS 2019 Workshop



Call for Papers

Technical Program

Robots in the Wild: Challenges in Deploying Robust Autonomy for Robotic Exploration

Venue Information

This workshop will be a part of the Robotics: Science and Systems (RSS) conference which will be held at Messe Freiburg, Freiburg im Breisgau, Germany, between June 22-26, 2019.

  • Workshop date: Sunday, June 23, 2019.
  • Location: Building 101, Room 02 016/018, Faculty of Engineering, Freiburg im Breisgau, Germany.

  • Submission cut-off (extended): May 30, 2019 June 7, 2019 (Anywhere on Earth).
  • Notification of acceptance (rolling basis): within two weeks of submission, until June 10, 2019.
  • Camera-ready paper due: June 15, 2019.
  • Workshop day: June 23, 2019.


New 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. 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 researchers to discuss the following themes:

  1. What challenges exist at the frontiers of robotic exploration of unstructured and extreme environments?
  2. How can we tie together the categories of systems, methods, and devices to address relevant scientific questions in such environments?
  3. How can we deal with the algorithmic challenges from the perspective of planning, learning, and decision-making for long-term autonomy of robots in extreme environments?


  1. System consideration for exploration of extreme environments such as underwater and benthic habitats, hot-springs, volcanoes, asteroids, and planetary surfaces.
  2. Challenges in environmental monitoring, precision agriculture, and disaster response.
  3. Multi-robot learning and coordination for environmental modeling.
  4. Underground and underwater mapping, space missions and planetary robots.
  5. Novelty, anomaly, and change detection.
  6. Decision-theoretic approaches for active sensing and physical sample (specimen) retrieval.
  7. Sampling algorithms and strategies, e.g., opportunistic sampling, non-myopic sampling.
  8. Online exploration algorithms: theory, experiments and field studies.