My interest is in autonomous systems and robotics, with a focus on AI, machine learning, computer vision and perception, safety-critical autonomy, and autonomy in unstructured environments. My graduate research explored methods to prepare autonomous vehicles for scenarios missing from datasets. I focused on dynamic small-object detection; in my research, it was pets. The idea was that the application could extend to small children and other missing or unlikely scenarios that standard datasets overlook. The current data available for training is a constraint when it doesn’t reflect the reality of the environment. The challenge extends beyond autonomous systems; when operating in unfamiliar environments, they may encounter conditions that could not be fully anticipated during development. My future goal is to focus my knowledge on research that supports long-term research that requires autonomous systems. Unexplored areas remain that way because of their inaccessibility to humans and unpredictable conditions.
Publications:
M. Strautkalns “Object Detection for Pets with Application to Autonomous Vehicles.” 16th Workshop on Planning, Perception and Navigation for Intelligent Vehicles (PPNIV 2026) , held in conjunction with the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026), Pittsburgh, PA, 2026.
M. Strautkalns, P. Robinson, “Web Based Prognostics and 24/7 Monitoring,” in Proc. Annual Conference of the Prognostics and Health Management Society, New Orleans, LA, USA, Oct. 2013.