4 accepted papers
The Michigan Robotics MBot is a low-cost mobile robot platform that has been used to train over 1,400 students in autonomous navigation since 2014 at the University of Michigan and our collaborating colleges. The MBot platform was designed to meet the needs of teaching robotics at scale to match the…
Articulated objects pose a unique challenge for robotic perception and manipulation. Their increased number of degrees-of-freedom makes tasks such as localization computationally difficult, while also making the process of realworld dataset collection unscalable. With the aim of addressing these sca…
Visual perception tasks often require vast amounts of labelled data, including 3D poses and image space segmen-tation masks. The process of creating such training data sets can prove difficult or time-intensive to scale up to efficacy for general use. Consider the task of pose estimation for rigid o…
Robots working in human environments must be able to perceive and act on challenging objects with articulations, such as a pile of tools. Articulated objects increase the dimensionality of the pose estimation problem, and partial observations under clutter create additional challenges. To address th…