We encourage submissions of article that address the role of energy principles in robotic control and learning, including but not limited to the following topics:

• Passivity-Based Control

• Virtual Energy Tanks

• Time-Domain Passivity Control

• Port-Based Modeling and Port-Hamiltonian Theory

• Mechanical Energy and Power Flow Analysis and Regulation

• Passivity Analysis and Passivization of Control Schemes

• Energy/Power-Based Safety Metrics for Physical Interaction

• Physics-Informed Machine Learning with Energy Priors

• Lagrangian, Hamiltonian, and Port-Hamiltonian Neural Networks

• Integration of Machine Learning and Port-Hamiltonian Theory

• Reinforcement Learning with Energy-Based Policies