Abstract:
Multirobotic management can involve communications between a command or leader robot and one or more client or follower robots through a cloud computing system. In an example implementation, a leader robot can receive first sensory data captured by a first follower robot and second sensory data captured by a second follower robot, determine a command function based on at least one of the first sensory data and the second sensory data, and communicate with at least one of the first follower robot and the second follower robot based on the command function.
Abstract:
Methods and systems for determining a status of a component of a device are provided. An example method includes triggering an action of a component of a device, and responsively receiving information associated with the action of the component from a sensor. The method further includes a computing system having a processor and a memory comparing the information with calibration data and determining a status of the component based on the comparison. In some examples, the calibration data may include information derived from data received from a pool of one or more devices utilizing same or similar components as the component. The determined status may include information associated with a performance of the component with respect to performances of same or similar components of the pool of devices. In one example, the device may self-calibrate the component based on the status.
Abstract:
Methods and systems for determining a status of a component of a device are provided. An example method includes triggering an action of a component of a device, and responsively receiving information associated with the action of the component from a sensor. The method further includes a computing system having a processor and a memory comparing the information with calibration data and determining a status of the component based on the comparison. In some examples, the calibration data may include information derived from data received from a pool of one or more devices utilizing same or similar components as the component. The determined status may include information associated with a performance of the component with respect to performances of same or similar components of the pool of devices. In one example, the device may self-calibrate the component based on the status.
Abstract:
Methods and systems for proactively preventing hazardous or other situations in a robot-cloud interaction are provided. An example method includes receiving information associated with task logs for a plurality of robotic devices. The task logs may include information associated with tasks performed by the plurality of robotic devices. The method may also include a computing system determining information associated with hazardous situations based on the information associated with the task logs. For example, the hazardous situations may comprise situations associated with failures of one or more components of the plurality of robotic devices. According to the method, information associated with a contextual situation of a first robotic device may be determined, and when the information associated with the contextual situation is consistent with information associated with the one or more hazardous situations, an alert indicating a potential failure of the first robotic device may be provided.
Abstract:
Methods and systems for allocating tasks to robotic devices are provided. An example method includes receiving information associated with task logs for a plurality of robotic devices and in a computing system configured to access a processor and memory, determining information associated with a health level for the plurality of robotic devices based on the information associated with the task logs. A health level for a given robotic device may be proportional to a current level of ability to perform a function, which may change over a lifespan of the given robotic device. Information associated with a plurality of tasks to be performed by one or more or the robotic devices may also be determined. The computing system may optimize an allocation of the plurality of tasks such that a high precision task may be allocated to a robotic device having a greater current health level than another robotic device.
Abstract:
Methods and systems for robot cloud computing are described. Within examples, cloud-based computing generally refers to networked computer architectures in which application execution and storage may be divided, to some extent, between client and server devices. A robot may be any device that has a computing ability and interacts with its surroundings with an actuation capability (e.g., electromechanical capabilities). A client device may be configured as a robot including various sensors and devices in the forms of modules, and different modules may be added or removed from robot depending on requirements. In some example, a robot may be configured to receive a second device, such as mobile phone, that may be configured to function as an accessory or a “brain” of the robot. A robot may interact with the cloud to perform any number of actions, such as to share information with other cloud computing devices.
Abstract:
Methods and systems for proactively preventing hazardous or other situations in a robot-cloud interaction are provided. An example method includes receiving information associated with task logs for a plurality of robotic devices. The task logs may include information associated with tasks performed by the plurality of robotic devices. The method may also include a computing system determining information associated with hazardous situations based on the information associated with the task logs. For example, the hazardous situations may comprise situations associated with failures of one or more components of the plurality of robotic devices. According to the method, information associated with a contextual situation of a first robotic device may be determined, and when the information associated with the contextual situation is consistent with information associated with the one or more hazardous situations, an alert indicating a potential failure of the first robotic device may be provided.
Abstract:
Methods and devices are disclosed for monitoring environmental conditions in one or more environments. In one embodiment, the method includes maintaining a plurality of environmental-condition thresholds, each of which corresponds to an environmental condition and is predetermined based on data corresponding to the environmental condition that is received from a plurality of robots. The method further includes receiving from a first robot first data corresponding to a first environmental condition in a first environment. The method may still further include making a first comparison of the first data and a first environmental-condition threshold corresponding to the first environmental condition and, based on the first comparison, triggering a notification. Triggering the notification may comprise transmitting to the robot instructions to transmit the notification to at least one of a call center and a remote device.
Abstract:
Methods and systems for proactively preventing hazardous or other situations in a robot-cloud interaction are provided. An example method includes receiving information associated with task logs for a plurality of robotic devices. The task logs may include information associated with tasks performed by the plurality of robotic devices. The method may also include a computing system determining information associated with hazardous situations based on the information associated with the task logs. For example, the hazardous situations may comprise situations associated with failures of one or more components of the plurality of robotic devices. According to the method, information associated with a contextual situation of a first robotic device may be determined, and when the information associated with the contextual situation is consistent with information associated with the one or more hazardous situations, an alert indicating a potential failure of the first robotic device may be provided.
Abstract:
Methods and systems for proactively preventing hazardous or other situations in a robot-cloud interaction are provided. An example method includes receiving information associated with task logs for a plurality of robotic devices. The task logs may include information associated with tasks performed by the plurality of robotic devices. The method may also include a computing system determining information associated with hazardous situations based on the information associated with the task logs. For example, the hazardous situations may comprise situations associated with failures of one or more components of the plurality of robotic devices. According to the method, information associated with a contextual situation of a first robotic device may be determined, and when the information associated with the contextual situation is consistent with information associated with the one or more hazardous situations, an alert indicating a potential failure of the first robotic device may be provided.