PATENT CLAIM ANALYSIS

Application Number: 15967240
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-08
Patent Classification: ["700", "257000"]

Abstract:
Apparatus and methods for training and controlling of, for instance, robotic devices. In one implementation, a robot may be trained by a user using supervised learning. The user may be unable to control all degrees of freedom of the robot simultaneously. The user may interface to the robot via a control apparatus configured to select and operate a subset of the robot's complement of actuators. The robot may comprise an adaptive controller comprising a neuron network. The adaptive controller may be configured to generate actuator control commands based on the user input and output of the learning process. Training of the adaptive controller may comprise partial set training. The user may train the adaptive controller to operate first actuator subset. Subsequent to learning to operate the first subset, the adaptive controller may be trained to operate another subset of degrees of freedom based on user input via the control apparatus.

Claim (Index 21):
A method of training an adaptive controller apparatus of a robot, the robot comprising first and second degrees of freedom, the method comprising:\n during a first operational iteration, in response to selecting a first actuator from a plurality of actuators, the first actuator being associated with a first degree of freedom:\n receiving a first computerized teaching signal, the first teaching signal being provided by a remote interface control element and configured to train the first degree of freedom; \n receiving a sensory input corresponding to a context of the robot via a sensor; \n causing the controller apparatus to produce a first computerized instruction signal based at least on the context; \n combining the first computerized teaching signal with the first computerized instruction signal based at least on the context to output a first computerized control signal, the first computerized control signal being configured to operate the robot in the first degree of freedom to execute a first action without operation in a second degree of freedom; and \n causing the controller apparatus to adjust a learning parameter based at least on a first performance relating to the first action and a target action; and \n during a subsequent iteration, in response to selecting a second actuator from the plurality of actuators, the second actuator being associated with the second degree of freedom:\n receiving a second computerized teaching signal, the second computerized teaching signal being provided by the remote interface and configured to train the second degree of freedom; \n causing the controller apparatus to produce a second computerized instructional signal based at least on the context; \n combining the second computerized teaching signal with the second computerized instruction signal based at least on the context to output a second computerized control signal, the second computerized control signal being different from the computerized control signal and configured to operate the robot in the second degree of freedom to execute a second action without operation in the first degree of freedom; and \n causing the controller apparatus to produce a third computerized control signal based at least on the context and the adjusted learning parameter, the third computerized control signal being configured to operate the first degree of freedom; \n wherein the second and the third computerized control signals cooperate to cause execution of the target action, the target action comprising at least operation in both the first and second degrees of freedom.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 91.0
- Lexical Diversity: 2.48485
- Patent Class: 700.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14070269', '14070114', '13918620', '14613237', '13918338']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4804155828146192
- 35 USC 102 Novelty (BERT): 0.5565764550151219
- Combined Prediction Score: 0.4880316700346696
- Mean Citation Score: 367.526456
- Max Citation Score: 453.5272
- Similarity Product: 396.2885169124604

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test