EnergyEfficient Locomotion Strategies and Performance Benchmarks using Point Mass Tensegrity Dynamics This work introduces a novel 12motor pairedcable actuation scheme to achieve rolling locomotion with a spherical tensegrity structure. Using a new point mass tensegrity dynamic formulation which we present, we utilize Model Predictive Control to generate optimal stateaction trajectories for benchmark evaluation. In particular, locomotive performance is assessed based on the practical criteria of rolling speed, energy efficiency, and directional trajectorytracking accuracy. Through simulation of 6motor, 12motor paired cable, and 24motor fullyactuated policies, we demonstrate that the 12motor schema is superior to the 6motor policy in all benchmark categories, comparable to the 24motor policy in rolling speed, and is over five times more energy efficient than the fullyactuated 24motor configuration.

Energy Conscious Overactuated MultiAgent Payload Transport Robot: Simulations and Preliminary Physical Validation In this work, we consider a multiwheeled payload transport system. Each of the wheels can be selectively actuated. When they are not actuated, wheels are free moving and do not consume battery power. The payload transport system is modeled as an actuated multiagent system, with each wheelmotor pair as an agent. Kinematic and dynamic models are developed to ensure that the payload transport system moves as desired. We design optimization formulations to decide on the number of wheels to be active and which of the wheels to be active so that the battery is conserved and the wear on the motors is reduced. Our multilevel control framework over the agents ensures that nearoptimal number of agents is active for the payload transport system to function. Through simulation studies we show that our solution ensures energy efficient operation and increases the distance traveled by the payload transport system, for the same battery power. We have built the payload transport system and provide results for preliminary experimental validation.