A circuit arrangement for switching an electrical load comprising an electrical switching element with a control input and an output; a control unit connected to the control input to drive the electrical switching element, in a first switching state, to generate a first output signal forming a switch-on signal for the load and, in a second switching state, to generate a second output signal, smaller than the first output signal, forming a switch-off signal for the electrical load; a safety output connected electrically to the electrical switching element output and to which the electrical load is connected; a decoupling apparatus arranged between the electrical switching element output and the safety output; a first output signal detecting apparatus connected to the electrical switching element output; and a second output signal detecting apparatus arranged in a circuit path between the decoupling apparatus and the safety output.

A data driven approach for fault detection in robotic actuation is disclosed. Here, a set of robotic tasks are received and analyzed by a Deep Learning (DL) analytics. The DL analytics includes a stateful (Long Short Term Memory) LSTM. Initially, the stateful LSTM is trained to match a set of activities associated with the robots based on a set of tasks gathered from the robots in a multi robot environment. Here, the stateful LSTM utilizes a master slave framework based load distribution technique and a probabilistic trellis approach to predict a next activity associated with the robot with minimum latency and increased accuracy. Further, the predicted next activity is compared with an actual activity of the robot to identify any faults associated robotic actuation.

A circuit arrangement for switching an electrical load comprising an electrical switching element with a control input and an output; a control unit connected to the control input to drive the electrical switching element, in a first switching state, to generate a first output signal forming a switch-on signal for the load and, in a second switching state, to generate a second output signal, smaller than the first output signal, forming a switch-off signal for the electrical load; a safety output connected electrically to the electrical switching element output and to which the electrical load is connected; a decoupling apparatus arranged between the electrical switching element output and the safety output; a first output signal detecting apparatus connected to the electrical switching element output; and a second output signal detecting apparatus arranged in a circuit path between the decoupling apparatus and the safety output.

A data driven approach for fault detection in robotic actuation is disclosed. Here, a set of robotic tasks are received and analyzed by a Deep Learning (DL) analytics. The DL analytics includes a stateful (Long Short Term Memory) LSTM. Initially, the stateful LSTM is trained to match a set of activities associated with the robots based on a set of tasks gathered from the robots in a multi robot environment. Here, the stateful LSTM utilizes a master slave framework based load distribution technique and a probabilistic trellis approach to predict a next activity associated with the robot with minimum latency and increased accuracy. Further, the predicted next activity is compared with an actual activity of the robot to identify any faults associated robotic actuation.