Large load manipulation and controller design with flexible joint manipulators

Abstract

Recent years have seen an increased interest in the use of flexible joint robots. This is due to wider use of collaborative and space robots. Flexibility is desired for collaborative robots because the inherent compliance makes interactions with humans safer. Space manipulator flexibility results from harmonic drives used to amplify the torque generated by the small actuators used to keep arm mass low for launch. Both situations require precise tracking of desired movements. However, this is difficult to achieve due to the inherent nonlinearity of flexible joint manipulators. There exist model-based and neural network based methods of controller design. However, these methods may result in complex controllers that require a high computational load. In space applications, there exist computational limitations that prevent the use of such control methods. For this reason, most space manipulators use simple controllers such as PID. Tuning the gains is difficult not only because of the arm nonlinearity but also because the arm operates both without and with large loads. Gain scheduling may be used to address the various operation modes. However, it would be desirable to have a single set of controller gains to prevent non-smooth transitions in controller output resulting from the gain changes. Whether designing one set or multiple set of gains, the tuning process can be very time consuming. Common methodologies require understanding of complex mathematics (such as for H-infinity methods) or a lot of active time from the control designer (such as hand-tuning). Therefore a methodology that can be implemented with basic controller design knowledge and consumes less of the controller designer's time is desirable. This thesis seeks to develop a methodology to generate robust, simple controllers for flexible joint robots that achieve the desired performance while operating both without and with a large load. The methodology consists of experiment design to gather experimental frequency response data, path generation, trajectory generation, and optimization problem formulation for controller design. The methodology is tested using a simulated arm and Rethink's Baxter robot. The simulated arm is an approximation to a space manipulator with seven degrees of freedom and joint flexibility. The simulation is performed using Simulink and Simscape Multibody. Baxter is a dual-arm industrial robot with each arm containing seven degrees of freedom. Baxter's joint flexibility results from series elastic actuators.