- Number
- 11385635
- Published
- 2022-07-12
- Filed
- 2019-05-08
- Assignee
- Disney Enterprises, Inc.
- Inventors
- Nocon; Nathan D., Panec; Timothy M., Medrano; Tritia V., Wong; Clifford, Barone; Nicholas F., Baumbach; Elliott H.
- CPC
- A63H30/04; G05B13/0265; G05D1/0011; G05D1/0016; G05D1/0027; G05D1/0033
- Verdict
- High Hardware
- Source
- Google Patents · FreePatentsOnline
The keeper's note
Autonomous flying-drone toy hardware with directional alignment control.
Abstract
Embodiments provide for autonomous drone play and directional alignment by in response to receiving a command for a remotely controlled device to perform a behavior, monitoring a first series of actions performed by the remotely controlled device that comprise the behavior; receiving feedback related to how the remotely controlled device performs the behavior, wherein the feedback is received from at least one of a user, a second device, and environmental sensors; updating, according to the feedback, a machine learning model used by the remotely controlled device to produce a second, different series of actions to perform the behavior; and in response to receiving a subsequent command to perform the behavior, instructing the remotely controlled device to perform the second series of actions.
Background
BACKGROUND (1) The remote manipulation and control of devices via voice commands relies on the device being able to properly identify the command from the utterance and to perform the command within desired conditions. Devices, however, can be slower and less precise when responding to voice commands than compared to manual commands input via a controller (e.g., keys, joysticks, mice). SUMMARY (2) The adjustable control for autonomous devices via voice commands is provided herein. One or more remotely controlled devices may receive commands included in an utterance from a user in addition to or instead of manual commands (e.g., via a joystick, button, or mouse). A voice command may specify an action or a behavior that the autonomous device is to perform. For example, an action command may specify to one or more devices to “move forward three feet,” and the device(s) will attempt to move forward three feet. A behavior command, however, may specify a series of action commands or variations of action commands. For example, a behavior command may specify “return to base,” and the device will attempt to move to the location designated as the “base,” either via the most direct route or a different route, depending on the behavior preference for completing the command. In another example, a behavior command may specify “evade player two,” and a first device will attempt to stay away from a second device (designated as player two), and the distance and maneuvers that the first device
Claims
1. A method, comprising: in response to receiving a command for a remotely controlled device to perform a behavior, identifying a first series of actions that are grouped in a sequence to define the behavior, wherein each action of the first series of actions is a user-directed action for the remotely controlled device to perform in the sequence taught by a user to a machine learning model; monitoring a performance of the first series of actions when executed by the remotely controlled device, wherein the remotely controlled device performs each action of the first series of actions at a base speed for the actions of the first series of actions and for a base duration for the actions of the first series of actions; receiving feedback related to how the remotely controlled device performs the behavior, wherein the feedback is received from at least one of the user, a second device, or environmental sensors; updating, according to the feedback, the machine learning model used by the remotely controlled device to produce a second series of actions to perform the behavior that is different from the first series of actions; and in response to receiving a subsequent command to perform the behavior, instructing the remotely controlled device to perform the second series of actions. ||
10. A system, comprising: a processor; and a memory, including instructions that when performed by the processor enable the system to: in response to receiving a command for a remotely controlled device to perform a behavior, identify a first series of actions that are grouped in a sequence to define the behavior, wherein each action of the first series of actions is a user-directed action for the remotely controlled device to perform in the sequence taught by a user to a machine learning model; monitor a performance of the first series of actions when executed by the remotely controlled device, wherein the remotely controlled device performs each action of the first series of action at a base speed for base duration; receive feedback related to how the remotely controlled device performs the behavior, wherein the feedback is received from at least one of the user, a second device, or environmental sensors; update, according to the feedback, the machine learning model used by the remotely controlled device to produce a second series of actions to perform the behavior that is different from the first series of actions; and in response to receiving a subsequent command to perform the behavior, instruct the remotely controlled device to perform the second series of actions. ||
15. A non-transitory computer-readable medium containing computer program code that, when executed by operation of one or more computer processors, performs an operation comprising: in response to receiving a command for a remotely controlled device to perform a behavior, identifying a first series of actions that are grouped in a sequence to define the behavior, wherein each action of the first series of actions is a user-directed action for the remotely controlled device to perform in the sequence taught by a user to a machine learning model; monitoring a performance of the first series of actions when executed by the remotely controlled device, wherein the remotely controlled device performs each action of the first series of actions at a base speed for the first series of actions and for a base duration for the first series of actions; receiving feedback related to how the remotely controlled device performs the behavior, wherein the feedback is received from at least one of the user, a second device, or environmental sensors; updating, according to the feedback, the machine learning model used by the remotely controlled device to produce a second series of actions to perform the behavior that is different from the first series of actions; and in response to receiving a subsequent command to perform the behavior, instructing the remotely controlled device to perform the second series of actions.