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Wells, William W.

Publications and source records attributed to Wells, William W..

Reinforcement Learning for Energy-Movement Optimization in Arduino-Based Robotics

Our goal is to develop a learning method for an Arduino-based robotthat maximizes travel distance and minimizes energy expenditure. • Will implement State ActionReward State Action (SARSA) reinforcement learning algorithm • Learning steps informed by state of environment • Rewards good decisions and punishes bad ones.

Gilmore, Blake↗

November 2019 Initial Deployment of LiDAR in the H-Canyon Exhaust Tunnel

The H-Canyon Exhaust Tunnel (CAEX) structure is periodically inspected under the Structural Integrity Program using camera equipped crawlers or poles to remotely perform visual inspections. To explore the use of enhanced inspection methods a “Proof of Concept” using the Light Detection and Ranging (LiDAR) technology was performed over a 2-day period in November 2019. The purpose of the “Proof of Concept” deployment was to confirm whether a commercially available LiDAR unit could successfully operate and remotely transmit data from the tunnel CAEX environment and whether the data would provide quantitative information to establish baseline measurements. The LiDAR performance requirement was a measurement accuracy of ± 0.25-inches over a 30-foot distance. This report documents the work activities leading to the deployment, the deployment and processing of data, lessons learned from the deployment and the post data processing methods that will be applied to future deployments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗