  The work presented here is a novel biological approach for the compliant
control of a robotic arm in real time (RT). We integrate a spiking cerebellar
network at the core of a feedback control loop performing torque-driven
control. The spiking cerebellar controller provides torque commands allowing
for accurate and coordinated arm movements. To compute these output motor
commands, the spiking cerebellar controller receives the robot's sensorial
signals, the robot's goal behavior, and an instructive signal. These input
signals are translated into a set of evolving spiking patterns representing
univocally a specific system state at every point of time.
Spike-timing-dependent plasticity (STDP) is then supported, allowing for
building adaptive control. The spiking cerebellar controller continuously
adapts the torque commands provided to the robot from experience as STDP is
deployed. Adaptive torque commands, in turn, help the spiking cerebellar
controller to cope with built-in elastic elements within the robot's actuators
mimicking human muscles (inherently elastic). We propose a natural integration
of a bio inspired control scheme, based on the cerebellum, with a compliant
robot. We prove that our compliant approach outperforms the accuracy of the
default factory-installed position control in a set of tasks used for
addressing cerebellar motor behavior: controlling six degrees of freedom (DoF)
in smooth movements, fast ballistic movements, and unstructured scenario
compliant movements.
