This paper presents a data-based approach to control robotic systems with partially-observed feedback. First, an open-loop optimization problem is solved to generate the nominal trajectory and then a linear time-varying Autoregressive–Moving-Average (ARMA) model of the system is calculated along the trajectory from the output measurement data. The system is then described in information state, which contains input-output information of the past few steps. Finally, a feedback gain which is calculated by solving a specific LQG problem along the nominal trajectory. The separate design of the open-loop and the closed-loop problem is used following the Decoupled Data-based Control (D2C) approach. Simulation results are also shown for complex models with fluid-structure interaction in the presence of both process and measurement noise.

Feedback control problems pertaining to the control of tensegrity robotic systems are detailed in this paper. The unique problems that arise due to the positivity of the string tensions required to maintain the static stability and desirable stiffness of the structural system are shown to bring about interesting opportunities to optimize for the redundancy in the actuation process. The static stability consideration, coupled with the nonlinear dynamics and the sensor models introduce additional algebraic constraints in implementation of both kinematic and model based dynamic controllers for tensegrity systems. Approaches to develop kinematic and dynamic control techniques are detailed in this paper. A bench top experimental setup consisting of a simple tensegrity system is utilized to demonstrate the efficacy of the output feedback control approach developed in the paper. Near real time image measurements are utilized to drive the output error used in the control scheme.

A robot with the ability to traverse complex duct systems requires a large range of controllable motions as well as the ability to grip the duct walls in vertical shafts. We present a tensegrity robot with two linked tetrahedral frames, each containing a linear actuator, connected by a system of eight actuated cables. The robot climbs by alternately wedging each tetrahedron within the duct and moving one tetrahedron relative to the other. We first introduce our physical prototype, called DuCTT (Duct Climbing Tetrahedral Tensegrity). We next discuss the inverse kinematic control strategy used to actuate the robot and analyze the controller's capabilities within a physics simulation. Finally, we discuss the hardware prototype and compare its performance with simulation.