Training an autonomous robot using previously captured data
OwnerHeinz Hemkeninventor
Life of this patent
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Abstract
Using various embodiments, an autonomous robot using data captured from a living subject are disclosed. In one embodiment, an autonomous robot can be trained using previously captured sensor data by receiving the sensor data, processing the sensor data and transmitting control signals to cause a movement in at least one portion of the autonomous robot. The movement can be related to an interaction of the autonomous robot with its surroundings, wherein the movement generates movement data. Thereafter, a predictive analysis can be performed on the movement data to learn a capability of generating actions that are spontaneous and adaptive to an immediate environment of the autonomous robot.
Claims18
A method to train an autonomous robot using previously generated sensor data, comprising:
- receiving the previously generated sensor data, by a processing system coupled to the autonomous robot;
- processing the previously generated sensor data and transmitting control signals to cause a movement in at least one portion of the autonomous robot, the movement related to an interaction of the autonomous robot with its surroundings, wherein the movement generates movement data;
- performing a predictive analysis on the movement data to learn a capability of generating actions that are spontaneous and adaptive to an immediate environment of the autonomous robot;
- wherein the predictive analysis is derived from at least one neural network and wherein the previously generated sensor data is further transmitted to at least one secondary neural network and wherein an output of the at least one secondary neural network causes refined movements that imitate intelligent behavior or action by the autonomous robot.
A non-transitory computer readable medium comprising instructions which when executed by a processing system executes a method to train an autonomous robot using previously generated sensor data, comprising:
- receiving the previously generated sensor data;
- processing the previously generated sensor data and transmitting control signals to cause a movement in at least one portion of the autonomous robot, the movement related to an interaction of the autonomous robot with its surroundings, wherein the movement generates movement data;
- performing a predictive analysis on the movement data to learn a capability of generating actions that are spontaneous and adaptive to an immediate environment of the autonomous robot;
- wherein the predictive analysis is derived from at least one neural network and wherein the previously generated sensor data is further transmitted to at least one secondary neural network and wherein an output of the at least one secondary neural network causes refined movements that imitate intelligent behavior or action by the autonomous robot.
A system comprising:
- an autonomous robot;
- a processing system having at least one hardware core coupled to the autonomous robot, configured to:
- receive previously generated sensor data;
- process the previously generated sensor data and transmitting control signals to cause a movement in at least one portion of the autonomous robot, the movement related to an interaction of the autonomous robot with its surroundings, wherein the movement generates movement data;
- and
- perform a predictive analysis on the movement data to learn a capability of generating actions that are spontaneous and adaptive to an immediate environment of the autonomous robot;
- wherein the predictive analysis is derived from at least one neural network and wherein the previously generated sensor data is further transmitted to at least one secondary neural network and wherein an output of the at least one secondary neural network causes refined movements that imitate intelligent behavior or action by the autonomous robot.
Dependencies are inferred from the claim text.