CoHOG: A Light-Weight, Compute-Efficient, and Training-Free Visual Place Recognition Technique for Changing Environments
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2020.2969917
Abstract: This letter presents a novel, compute-efficient and training-free approach based on Histogram-of-Oriented-Gradients (HOG) descriptor for achieving state-of-the-art performance-per-compute-unit in Visual Place Recognition (VPR). The inspiration for this approach (namely CoHOG) is based on the convolutional… read more here.
Keywords: place recognition; place; training free; efficient training ... See more keywords
Fast and Compute-Efficient Sampling-Based Local Exploration Planning via Distribution Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3186511
Abstract: Exploration is a fundamental problem in robotics. While sampling-based planners have shown high performance and robustness, they are oftentimes compute intensive and can exhibit high variance. To this end, we propose to learn both components… read more here.
Keywords: robotics; fast compute; compute efficient; sampling based ... See more keywords