Summer@LSTS 2020 – Session #1 with Kanna Rajan (LSTS FEUP)

Summer@LSTS 2020 started on August 7th, 2020, 2:00-3:30 PM UTC, with Kanna Rajan, who presented Explorations in AI for Maritime Robotics.

Ocean Sciences the world over is at a cusp, with a move from the Expeditionary to the Observatory mode of doing science. Recent policy decisions in the United States, are pushing the technology for persistent observation and sampling which hitherto had been either economically unrealistic or unrealizable due to technical constraints. With the advent of ocean observatories, a number of key technologies have however proven to be promising for sustained ocean presence. In this context robots will need to be contextually aware and respond rapidly to evolving phenomenon, especially in coastal waters due to the diversity of atmospheric, oceanographic and land-sea interactions not to mention the societal impact they have on coastal communities. They will need to respond by exhibiting scientific opportunism while being aware of their own limitations in the harsh oceanic environment. Current robotic platforms however have inherent limitations; pre-defined sequences of commands are used to determine what actions the robot will perform and when irrespective of the context. As a consequence not only can the robot not recover from unforeseen failure conditions, but they’re unable to significantly leverage their substantial onboard assets to enable scientific discovery.

To mitigate such shortcomings, we have designed, built, tested and deployed deliberative techniques to dynamically command autonomous underwater vehicles (AUVs) with deep roots in work to command and control deep space probes for NASA. Our effort is aimed to use a blend of generative and deliberative Artificial Intelligence Planning and Execution techniques to shed goals, introspectively analyze onboard resources and recover from failures. In addition we are working on Machine Learning techniques to adaptively trigger science instruments that will contextually sample the seas driven by scientific intent. The end goal is towards unstructured exploration of the subsea environments that are a rich trove of problems for autonomous systems. Our approach spans domains and not unduly specific to the ocean domain; the developed system is being used for a terrestrial personal robot at a Silicon Valley startup and is being tested on a Planetary rover test bed by the European Space Agency. Our work is a continuum of efforts from research at NASA to command deep space probes and Mars rovers, the lessons of which we have factored into the oceanic domain. In this talk I will articulate the challenges of working in this hostile underwater domain, lay out the differences and motivate our architecture for goal-driven autonomy on AUV’s and more recently on unmanned aerial vehicles (UAVs) for dual-use exploration and surveillance.

Kanna Rajan is a Visiting Professor, Faculty of Engineering, Univ. of Porto affiliated with the Underwater Systems Technology Lab. He was the Principal Researcher in Autonomy at the Monterey Bay Aquarium Research Institute ( a privately funded non-profit Oceanographic institute which he joined in October 2005. Prior to that he was a Senior Research Scientist for the Autonomous Systems and Robotics Area at NASA Ames Research Center Moffett Field, California.

At NASA Ames, he balanced programmatic and technical responsibilities. He was the Principal Investigator of the MAPGEN Mixed-Initiative Planning effort to command and control the Spirit and Opportunity rovers on the surface of the Red Planet. MAPGEN continues to be used to this day, twice daily in the mission-critical uplink process at the Jet Propulsion Laboratory in Pasadena. Kanna was one of the six principals of the Remote Agent Experiment (RAX) team, which designed, built, tested and flew the first closed-loop AI based control system on a spacecraft. The RA was the co-winner of NASA’s 1999 Software of the Year, the agency’s highest technical award (

His interests are in automated Planning/Scheduling, modeling and representation for real world planners and agent architectures for Distributed Control applications. Prior to joining NASA Ames, he was in the doctoral program at the NYU Courant Institute of Math Sciences. Prior to that he was at the Knowledge Systems group at American Airlines, helping build a Maintenance Routing scheduler (MOCA), which continues to be used by the airline 365 days of the year.

MAPGEN has been awarded NASA’s 2004 Turning Goals into Reality award under the Administrators Award category, a NASA Space Act Award, a NASA Group Achievement Award and a NASA Ames Honor Award. Kanna is the recipient of the 2002 NASA Public Service Medal and the First NASA Ames Information Directorate Infusion Award also in 2002. In Oct 2004, the Jet Propulsion Laboratory awarded him the NASA Exceptional Service Medal for his role on the Mars Exploration Rovers mission.

He was the Co-chair of the 2005 International Conference on Automated Planning and Scheduling (ICAPS), Monterey California and till recently the chair of the Executive Board of the International Workshop on Planning and Scheduling for Space. He has served on review panels for NASA, the Italian Space Agency, the Swedish Maritime Robotics Center, the European Space Agency and the US National Science Foundation.

If you need any additional information please send an email to Jose Luiz Moutinho.


Kanna Rajan

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