uncertainty and distributional shift.” Distributional shift deals with the transferability of training data between environments. “Let’s say I train my system in the Caribbean and then deploy it in the Arctic: will it go wrong because I trained it on a completely different dataset? That is an example of how you look at the applicability and appropriateness of your training datasets and your models for the situations you are putting these systems into,” she says. The IAA works with autonomous systems developers and researchers in Johns Hopkins University and beyond in an effort to build an understanding of assurance. “People often don’t recognise that they are doing assured autonomy, even if they are in the autonomy space,” LaPointe notes. “But they really are doing assured autonomy because the whole process of making sure their systems work correctly is the assurance. So we work with folks to understand what they are having a hard time with, and that is where we set our priorities in creating tools and methodologies to help them.” Safety testing Tools developed by the APL and other organisations are already available and in use. For example, the APL and the US government have developed the Range Adversarial Planning Tool (RAPT), a software framework that allows test engineers to identify safe operating envelopes for decision-making systems in simulated environments. With a deterministic system it is straightforward to put it in a particular mode to see whether it does what it is expected to do, LaPointe explains, but that does not suit AI operating in conditions of high uncertainty. “When you are testing an autonomous system at the ultimate mission or goal level you need a completely different type of tool to evaluate its performance,” she says. The RAPT focuses on finding tests that represent the thresholds of, for example, a UUV’s performance in scenarios that are known to demonstrate relevant changes in its behaviour. The tool identifies performance boundaries of the system under test through unsupervised learning methods, and it has been used to test the compliance of USVs with collision regulations, for example. The IAA has funded an enhancement to the RAPT in the form of a GUI. It helps engineers quickly visualise where changes to an autonomous system’s software has improved its performance and where it has not, LaPointe says. The IAA’s involvement with tools for developers is broadening. For example, it is working towards presenting what LaPointe describes as a life cycle-based roadmap of tools from multiple sources for project phases from requirements development through design and beyond, which have wide applicability. “It is important to have tools that are generalisable and, ultimately, tailorable, because every technology and application is going to have different needs,” she notes.” Ultimately, LaPointe wants the benefits of assured autonomy to help as many people as possible. “When I worked in the office of the Deputy Assistant Secretary of the Navy for Unmanned Systems, one of our colleagues was legally blind, so he couldn’t drive. For him, it was a personal issue to get assured autonomous cars on the road so that he could have a level of individual freedom and mobility. I think a lot about marginalised and vulnerable populations, and I am very focused on ensuring that those systems work for every segment of society.” 23 Uncrewed Systems Technology | August/September 2023 Born in Washington DC to a multi-generational naval family, Dr Cara LaPointe’s love of the ocean drew her into scuba diving in her early teens. That in turn drew her into the US Naval Academy, where she earned a bachelor’s degree in ocean engineering in 1997. She went on to earn a master’s in international development studies from the University of Oxford in 1999, followed by service at sea in engineering and navigation roles aboard destroyers in the Pacific Ocean. From 2003 to 2009 she was at the Massachusetts Institute of Technology, where she gained a master’s in ocean systems management, an engineer’s degree in naval construction and engineering, and a PhD in mechanical and oceanographic engineering jointly awarded by MIT and the Woods Hole Oceanographic Institution (WHOI). In the WHOI’s Deep Submergence Lab, she researched autonomous underwater vehicle navigation and sensor fusion algorithms. In 2009 she took up the post of a ship concept manager for the Navy, working on design, shipbuilding industrial base analysis and the shipboard integration of uncrewed and autonomous systems. In 2011, she joined the Littoral Combat Ship programme, first as a production engineer and then rising to deputy technical director of the programme. Other senior Navy posts followed, including deputy program manager for electric ships and chief of staff to the Deputy Assistant Secretary of the Navy for Unmanned Systems. Dr LaPointe founded emerging technology and strategy consulting firm Archytas in 2018, and remains its CEO. She took up the position of co-director of the Johns Hopkins Institute for Assured Autonomy and Intelligent Autonomous Systems programme manager at its Applied Physics Laboratory in January 2019. Cara LaPointe
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