APPARATUS AND METHODS FOR CONTROLLING OF ROBOTIC DEVICES

• US 20150032258A1
• Filed: 07/29/2013
• Published: 01/29/2015
• Est. Priority Date: 07/29/2013
• Status: Abandoned Application

• Current Assignee: Brain Corporation
• Original Assignee: Brain Corporation
• Inventors: Passot, Jean-Baptiste, Laurent, Patryk, Izhikevich, Eugene M.
• Application Number:
  US13/953,595
• Publication Number:
  US 20150032258A1
• Time in Patent Office: Days
• US Class Current: 700/250
• CPC Class Codes: B25J 9/1656 characterised by programming, planning systems for manipulators
• CPC Class Codes: G05B 2219/35444 Gesture interface, controlled machine observes operator, executes commands
• CPC Class Codes: G05B 2219/40116 Learn by operator observation, symbiosis, show, watch
• CPC Class Codes: G05D 1/0016 characterised by the operator's input device input arrangements for computing systems in general G06F3/00
• CPC Class Codes: G06N 3/008 based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. based on robots replicating pets or humans in their appearance or behaviour
• CPC Class Codes: G06N 3/049 Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs

Abstract

A robot may be trained based on cooperation between an operator and a trainer. During training, the operator may control the robot using a plurality of control instructions. The trainer may observe movements of the robot and generate a plurality of control commands, such as gestures, sound and/or light wave modulation. Control instructions may be combined with the trainer commands via a learning process in order to develop an association between the two. During operation, the learning process may generate one or more control instructions based on one or more gesture by the trainer. One or both the trainer or the operator may comprise a human, and/or computerized entity.

Claims

1. A non-transitory computer readable medium having instructions embodied thereon, the instructions being executable by one or more processors to:

cause a robot to execute a plurality of actions based on one or more directives;

receive information related to a plurality of commands provided by a trainer based on individual ones of the plurality of actions; and

associate individual ones of the plurality of actions with individual ones of the plurality of commands using a learning process.

2. The non-transitory computer readable medium of claim 1, wherein:

the robot comprises at least one actuator configured to be operated by a motor instruction;

individual ones of the one or more directives comprise the motor instruction provided based on input by an operator; and

the association is configured to produce a mapping between given command and a corresponding instruction.

3. The non-transitory computer readable medium of claim 1, wherein the instructions are further executable by one or more processors to cause provision of a motor instruction based on another command provided by the trainer.

4. A processor-implemented method of operating a robotic apparatus, the method being performed by one or more processors configured to execute computer program modules, the method comprising:

during at least one training interval;

providing, using one or more processors, a plurality of control instructions configured to cause the robotic apparatus to execute a plurality of actions; and

receiving, using one or more processors, a plurality of commands configured based on the plurality of actions being executed; and

during an operation interval occurring subsequent to the at least one training interval;

providing, using one or more processors, a control instruction of the plurality of control instructions, the control instruction being configured to cause the robotic apparatus to execute an action of the plurality of actions, the control instruction provision being configured based on a mapping between individual ones of the plurality of actions and individual ones of the plurality of commands.

5. The method of claim 4, wherein:

the plurality of control instructions is provided based on directives by a first entity in operable communication with the robotic apparatus;

the plurality of commands is provided by a second entity disposed remotely from the robotic apparatus; and

the control instruction is provided based on a provision by the second entity of a respective command of the plurality of commands.

6. The method of claim 5, further comprising:

causing a transition from the at least one training interval to the operational interval based on an event provided by the second entity;

wherein;

the first entity comprises a computerized apparatus configured to communicate the plurality of control instructions to the robotic apparatus; and

the robotic apparatus comprises an interface configured to detect the plurality of commands.

7. The method of claim 6, wherein:

the first entity comprises a human; and

individual ones of the plurality of commands comprise one or more of a human gesture, a voice signal, an audible signal, or an eye movement.

8. The method of claim 6, wherein:

the robotic apparatus comprises at least one actuator characterized by an axis of motion;

individual ones of the plurality of actions are configured to displace the actuator with respect to the axis of motion;

the interface comprises one or more of a visual sensing device, an audio sensor, or a touch sensor; and

the event is configured based on a timer expiration.

9. The method of claim 4, wherein:

the mapping is effectuated by an adaptive controller of the robotic apparatus operable by a spiking neuron network characterized by a learning parameter configured in accordance with a learning process;

the at least one training interval comprises a plurality of training intervals; and

for a given training interval of the plurality of training intervals, the learning parameter is determined based on a similarity measure between individual ones of the plurality of actions and respective individual ones of the plurality of commands.

10. The method of claim 9, wherein the learning parameter is determined based on multiple values of the similarity measure determined for multiple ones of the plurality of training intervals, individual ones of the multiple values of the similarity measure being determined based on a given one of the plurality of actions and a respective one of the plurality of commands occurring during individual ones of the multiple ones of the plurality of training intervals.

11. The method of claim 9, wherein the similarity measure is determined based on one or more of a cross-correlation determination, a clustering determination, a distance-based determination, a probability determination, or a classification determination.

12. The method of claim 4, wherein:

at least one training interval comprises a plurality of training intervals;

the mapping is effectuated by an adaptive controller of the robotic apparatus operable in accordance with a learning process; and

the learning process is configured based on one or more tables including one or more of a look up table, a hash-table, or a data base table, a given table being configured to store a relationship between given one of the plurality of actions and a respective one of the plurality of commands occurring during individual ones of the multiple ones of the plurality of training intervals.

13. The method of claim 4, wherein:

individual ones of the plurality of actions are characterized by a state parameter of the robotic apparatus; and

the plurality of actions is configured in accordance with a trajectory in a state space, the trajectory being characterized by variations in the state parameter between successive actions of the plurality of actions.

14. The method of claim 13, wherein the trajectory is configured based on a random selection of the state for individual ones of the plurality of actions.

15. The method of claim 4, wherein:

individual ones of the plurality of actions are characterized by a pair of state parameters of the robotic apparatus in a state space characterized by at least two dimensions; and

the plurality of actions is configured in accordance with a trajectory in a state space, the trajectory being characterized by variations in the state parameter between successive actions of the plurality of actions.

16. The method of claim 15, wherein the at least two dimensions are selected from the group consisting of coordinates in a two-dimensional plane, motor torque, motor rotational angle, motor velocity, and motor acceleration.

17. The method of claim 15, wherein the trajectory comprises a plurality of set-points disposed within the state-space, individual ones of the set-points being characterized by a state value selected prior to onset of the at least one training interval.

18. The method of claim 15, wherein the trajectory comprises a periodically varying trajectory characterized by multiple pairs of state values, the state values within individual pairs being disposed opposite one another relative to a reference.

19. The method of claim 4, further comprising:

during the at least one training interval;

providing at least one predicted control instruction based on a given command of the plurality of commands, the given command corresponding to a given control instruction of the plurality of control instructions;

determining a performance measure based on a similarity measure between the predicted control instruction and the given control instruction; and

causing a transition from the at least one training interval to the operational interval based on the performance measure breaching a transition threshold.

20. A computerized system comprising:

a robotic device comprising at least one motor actuator;

a control interface configured to provide a plurality of instructions for the actuator based on an signal from an operator;

a sensing interface configured to detect one or more training commands configured based on a plurality of actions executed by the robotic device based on the plurality of instructions; and

an adaptive controller configured to;

provide a mapping between the one or more training commands and the plurality of instructions; and

provide a control command based on a command by the trainer;

wherein the control command is configured to cause the actuator to execute a respective action of the plurality of actions.