Research Interests

In iRaL, we care for a trustworthy collaborative autonomy in dynamic, interactive, and adversarial environments. We care for impact on safety- and time-critical applications that necessitate trustworthiness, such as:

  • multi-target tracking, search and rescue, and persistent surveillance;
  • safe navigation of self-driving vehicles in crowded cities, and unknown (extraterrestrial) environments;
  • attack-susceptible satellite networks and flying multi-rotor vehicles.

We aim for a technological convergence between:

  • “cyber” capabilities for a distributed intelligence, driven by online learning for perception, (inter)action prediction, planning, and control, and
  • “physical” capabilities of novel self-reconfigurable aerospace systems.

We build on tools of learning, perception, control, as well as, of combinatorial, non-convex optimization, with the goal to:

  • identify fundamental optimization limits;
  • develop provably optimal algorithms;
  • build novel robotic platforms;
  • apply the research outcomes.


[Past Research | Publications | Honors & Awards]