3 accepted papers
In this work, we present a novel approach for modeling, and classifying between, the system load states introduced when constructing staged soft arm configurations. Through a two stage approach: (1) an LSTM calibration routine is used to identify the current load state then (2) a control input gener…
In this letter, we build on recent advances in deep learning to improve SE(3) transformations, enabling more accurate motion estimation in mobile robots. We propose using denoising autoencoders (DAEs) to address the challenges presented by modern LIDARs. Our proposed approach is comprised of two sta
In this work we develop a novel framework that enables the real-time 3D reconstruction of underwater environments using features from 2D sonar images. Due to noisy and low-resolution imagery as compared with standard cameras, automatic feature extractors for sonar images are not reliable in many sce…