Engineering topics
Publications and source records attributed to Filho, Faete J..
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.
Our goal is to teach a robot to walk in an energy efficient way. Inspired by nature [1], we create a reinforcement learning method that balances distance traveled and energy consumption, which we call “utility.” Further, each step is symmetric to ensure equal strides while walking straight. We achieve our goal by rewarding decisions that lead to the best utility over several training iterations.
The demand for a more capable electric power grid has increased due to greater energy generation and consumption. • Controlling energy flow bidirectionally with new technologies such as solid state transformers can meet this demand, improving power quality, efficiency, and grid security. • A human machine interface was created to control a medium voltage solid state transformer.