System dynamic design and control of the Plugless Robot Arm

Abstract

Current robots consume a lot of energy. The work required for a task is generally just a tiny fraction of the total energy consumed. Most energy wastefully dissipated. Design of the 2 degree of freedom (DoF) Plugless Robot Arm shows that clever design can reduce these energy losses to a tiny remaining fraction. The Plugless Arm is designed to perform a pick-and-place task displacing packages of 1 kg over a vertical distance of 1 m and some additional horizontal distance in a way that is capable of powering the full system.

Maximum energy recovery is achieved by the design of springs in parallel to the actuators such that minimal actuator currents lead to minimal electric heat losses. This requires simultaneous optimisation of the trajectory and the parallel elastic elements. In a Cartesian configuration a novel method is tested which allows for implicit optimisation of an elastic element without additional parameterisation. The optimal parallel spring characteristic can be expressed as a pure function of the trajectory if the system dynamics are defined as a function of position instead of time.

Afterwards the analytical optimal spring is replaced by a mechanism of low mechanical complexity showing similar energy characteristics. The mechanism is translated to a polar equivalent for the 2 DoF arm and optimised together with the trajectory of the arm. The optimal nominal trajectory is followed under undisturbed conditions when applying a pre-computed feedforward control signal to the actuators of the arm. Additional local optimal linear state feedback control is computed by means of Differential Dynamic Programming. All optimisation is done offline. Performance of the controller under disturbed conditions is tested in terms of accuracy as well as energy consumption.

The system achieves a nominal energy retrieval of 3.64 J per cycle of 2.5 s, which is sufficient to power a light controller, the necessary sensors and a special energy efficient gripper. Some energy is left which can be used by the controller to recover from disturbances which extract energy from the system. The controller is also able to recover additional energy from disturbances which add energy to the system.

The implementation of the controller is further optimised to achieve minimal computational energy consumption and memory requirements. By selective reduction of the control law, considerable data reduction is achieved with negligible impact on the controller performance.