Micah Corah



Micah is a postdoc at the NASA Jet Propulsion Laboratory with Dr. Ali Agha where he competed with team CoSTAR in the DARPA Subterranean Challenge. Previously, Micah completed a Ph.D. in Robotics at Carnegie Mellon University advised by Prof. Nathan Michael focusing on distributed perception planning and multi-robot exploration. Micah is deeply interested in problems related to navigation, perception planning, and control for mobile robots and especially aerial robot teams.

Speaker Links: Linkedin - Google Scholar - Twitter


Processes of observing unknown and uncertain objects and environments are pervasive in robotics applications spanning autonomous mapping, tracking, inspection, and cinematography. Further, autonomy is especially important to applications such as search and rescue as autonomous operation is critical to enable mobile robots to penetrate through rubble beyond the communication range of human operators. Moreover, teams of autonomous robots can improve situation awareness for responders and significantly improve response times. This talk will be split into two parts: The first part of this talk will focus on methods for informative planning and active perception for one or more robots, and the latter part of this talk will briefly review lessons learned while competing with team CoSTAR in the Finals of the DARPA Subterranean Challenge. Autonomous perception tasks such as mapping a building or tracking targets often produce optimization problems that are difficult to solve (NP-Hard) and yet highly structured. Taking advantage of structure can greatly simplify these problems such as by providing efficient and accurate objective evaluation or efficient distributed algorithms with strong suboptimality guarantees. The methods we will discuss enable individual robots and teams to navigate and observe unknown environments at high speeds while quickly and collectively adapting to information from new observations. Still, there are significant gaps between laboratory (and theoretic) settings and the field. The multi-robot systems deployed in the DARPA Subterranean Challenge Finals represent incredible advances in the ability of teams of robots to operate autonomously and intelligently in harsh and unstructured environments. Yet, the development of these systems is focused on reliability and redundancy, and simple methods that work well enough in practice often prevail over seemingly advanced methods. This talk will focus on the performance of these multi-robot aerial and ground systems in the competition and speculate on what to expect in the near future.

Papers and videos covered during the talk

  • Corah, Micah. (2020). Sensor Planning for Large Numbers of Robots. Diss. Carnegie Mellon University Pittsburgh, PA, 2020.link
  • Goel, K., Corah, M., Boirum, C., & Michael, N. (2021). Fast Exploration Using Multirotors: Analysis, Planning, and Experimentation.link - video simulation - video real
  • Corah, M., O’Meadhra, C., Goel, K., & Michael, N. (2019). Communication-Efficient Planning and Mapping for Multi-Robot Exploration in Large Environments. IEEE Robotics and Automation Letters, 4, 1715-1721.link
  • Exploring an office environment with fully distributed planning - video
  • Exploring a warehouse with distributed Gaussian mixture mapping - video