On robot compliance. A cerebellar control approach

The work of I. Abadía was supported by U. Granada and Junta Andalucía-FEDER. The work of F. Naveros and E. Ros were supported by the Spanish National Grant (MINECO-FEDER TIN2016-81041-R) and the EU HBP-SGA2, (H2020-RIA, 785907). The work of N. R. Luque was supported by a Juan de la Cierva Spanish fellowship (IJCI-2016-27385) ; Versión de submission ; 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 behaviour, 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 behaviour: controlling six degrees of freedom (DoF) in (i) smooth movements, (ii) fast ballistic movements and (iii) unstructured scenario compliant movements. ; Universidad de Granada ; Junta Andalucía ; FEDER ; MINECO-FEDER TIN2016-81041-R ; EU HBP-SGA2, (H2020-RIA, 785907) ; Juan de la Cierva (IJCI-2016-27385)