Factor graphs for Sensor Fusion in Robotics.
The OpenSAM Foundation (OSF) is a non-profit organization that seeks to advance the use of factor graphs for sensor fusion in robotics and computer vision applications.
We are starting a Youtube channel that we will gradually fill with short explainers. For now there are only two videos by Frank Dellaert, one from RSS and one from ECCV. However, Cyrill Stachniss is working on a 5-minute intro to factor graphs, and Frank is preparing something about Bayes trees. Stay tuned, and subscribe to the channel if interested!
Many computational problems in robotics have an optimization problem at their core. For example, in simultaneous localization and mapping (SLAM) and many other estimation problems we are after a maximum a posteriori estimate, i.e., we try to maximize posterior probability of the variables given a set of measurements. When attempting to act optimally, we try to maximize a performance index, or conversely minimize a penalty function. And even in classical planning, we are trying to find an assignment to a set of discrete variables that minimizes the plan length or optimizes for some other desirable property of the plan.