1. A method of determining a motor control signal for a robot based on an analysis of a sensor input, the method comprising: analyzing the sensor input based on a first transformation process applied based on a presence of one or more first features present in the sensor input with a first characteristic; analyzing the sensor input based on a second transformation process applied based on a presence of one or more second features present in the sensor input with a second characteristic, the second characteristic being different from the first characteristic; determining a feature history comprising a plurality of features determined based on at least the acts of analyzing the sensor input based on the first transformation process over a first time interval and analyzing the sensor input based on the second transformation process over a second time interval; normalizing each of the plurality of features using a statistical parameter determined from the feature history; providing a plurality of the normalized features to a classification process for detecting at least one relevant feature among the plurality of the normalized features, the at least one relevant feature being characterized by a relevancy parameter that is larger than a predetermined threshold; selecting from a plurality of control signals a motor control signal associated with the at least one relevant feature; and executing the selected motor control signal, thereby causing a target task to be performed by the robot; wherein the act of selecting the motor control signal is effectuated based on a prior contemporaneous occurrence of the motor control signal and the at least one relevant feature.
1. A method of determining a motor control signal for a robot based on an analysis of a sensor input, the method comprising: analyzing the sensor input based on a first transformation process applied based on a presence of one or more first features present in the sensor input with a first characteristic; analyzing the sensor input based on a second transformation process applied based on a presence of one or more second features present in the sensor input with a second characteristic, the second characteristic being different from the first characteristic; determining a feature history comprising a plurality of features determined based on at least the acts of analyzing the sensor input based on the first transformation process over a first time interval and analyzing the sensor input based on the second transformation process over a second time interval; normalizing each of the plurality of features using a statistical parameter determined from the feature history; providing a plurality of the normalized features to a classification process for detecting at least one relevant feature among the plurality of the normalized features, the at least one relevant feature being characterized by a relevancy parameter that is larger than a predetermined threshold; selecting from a plurality of control signals a motor control signal associated with the at least one relevant feature; and executing the selected motor control signal, thereby causing a target task to be performed by the robot; wherein the act of selecting the motor control signal is effectuated based on a prior contemporaneous occurrence of the motor control signal and the at least one relevant feature. 4. The method of claim 1 , wherein: the first transformation process comprises a sparsification operation comprising selecting one or more first features from a plurality of first outputs produced by the first transformation process based on the first characteristic; and the sparsification operation further comprises reducing a number of data elements by a factor of at least four.