Stanford Seminar - Robotic Autonomy and Perception in Challenging Environments

Christoffer Heckman
CU Boulder
January 17, 2020
Perception precedes action, in both the biological world as well as the technologies maturing today that will bring us autonomous cars, aerial vehicles, robotic arms and mobile platforms. The problem of probabilistic state estimation via sensor measurements takes on a variety of forms, resulting in information about our own motion as well as the structure of the world around us. In this talk, I will discuss some approaches that my research group has been developing that focus on estimating these quantities online and in real-time in extreme environments where dust, fog and other visually obscuring phenomena are widely present and when sensor calibration is altered or degraded over time. These approaches include new techniques in computer vision, visual-inertial SLAM, geometric reconstruction, nonlinear optimization, and even some sensor development. The methods I discuss have an application-specific focus to ground vehicles in the subterranean environment, but are also currently deployed in the agriculture, search and rescue, and industrial human-robot collaboration contexts.
View the full playlist: • Stanford AA289 - Robot...