Trainable convolutional network apparatus and methods for operating a robotic vehicle

A method of generating a predicted control output by an adaptive controller of a robotic apparatus comprising a predictor and a combiner, the method comprising:

• configuring the adaptive controller apparatus to detect an object in sensory input provided by a sensor of the robotic apparatus, the object detection causing generation of a control output based on a characteristic of the object;
• configuring the predictor to determine a predicted control output based on the characteristic of the object;
• configuring the combiner to determine a combined output based on a control input and the predicted control output, the combined output being characterized by a transform function;
• determining a performance measure based on the predicted control output and the combined output;
• updating one or more learning parameters of the adaptive controller in accordance with the performance measure;
• and
• configuring the adaptive controller to provide the combined output to the robotic apparatus, the combined output configured to cause the robotic apparatus to execute a maneuver in accordance with the characteristic of the object.

A computerized neuron network apparatus configured to provide a response based on analysis of visual input frames, the apparatus comprising:

• an input component comprising first portion of neurons configured to implement a convolutional operation on the visual input frames using a plurality of filter masks, the operation configured to produce convolved input frames;
• an output component comprising at least one output neuron configured to provide an output based on the at least one output neuron reaching a target state;
• a connection component configured to couple the input component to the at least one output neuron via an efficacy array;
• and
• a cost estimation component configured to determine a first similarity measure between a response and a target response;
• wherein:
• the response is configured based on the output;
• the first similarity measure determined based on a first analysis of a first frame of the visual input frames is configured to cause update of the neuron network, the update of the neuron network configured to increase a second similarity measure determined based on a second analysis of a second frame of the visual input frames subsequent to the first frame.

A method of operating a robotic device using a computerized neuron network having a plurality of layers of neurons, the method comprising:

• causing the robotic device to execute an action along a first trajectory in accordance with a first control signal, the first signal determined based at least on a sensory input;
• determining a performance measure based on an evaluation of the first trajectory relative to a target trajectory;
• updating one or more learning parameters of a first of the plurality of layers in accordance with information relating to the determined performance measure;
• and
• causing the robotic device to execute the action along a second trajectory in accordance with a second control signal, the second signal determined based at least on a sensory input and the updated one or more learning parameters, the second trajectory being closer to the target trajectory than the first trajectory.