Methods, systems, and computer programs are presented for executing a mission by an autonomous device to inspect an asset. One method includes an operation for obtaining a workflow. The workflow includes operations to be executed during a mission to be performed by a robot and a destination for sending data resulting from the mission. The method further includes an operation for generating a package after completion of the mission associated with the workflow. The package is self-contained and comprises information obtained during the mission that enables generation of results. The package comprises sensor information collected by one or more sensors, telemetry information obtained by the robot, information about assets associated with the mission, software version identifier for the package generation, and routing information for transmitting the package to the destination. The method further includes an operation for analyzing the information of the package to determine results for the mission.

The technology is directed to providing pick and place instructions to a robot. Sensor data including an image feed of a picking container in which at least one product is located may be output. An input indicating a selected product including at least one of the products located in the picking container may be received. A representation of the selected product and at least one image of the order container may be output for display. The representation of the product may be scaled relative to the at least one image of the order container. A place input corresponding to the position of the representation of the product at a packing location within the at least one image of the order container may be received and transmitted to a robot control system.

An intelligent system, such as an autonomous robot agent, includes systems and methods to learn various aspects about a task in response to instructions received from a human instructor, to apply the instructed knowledge immediately during task performance following the instruction, and to instruct other intelligent systems about the knowledge for performing the task. The learning is accomplished free of training the intelligent system. The instructions from the human instructor may be provided in a natural language format and may include deictic references. The instructions may be received while the intelligent system is online, and may be provided to the intelligent system in one shot, e.g., in a single encounter or transaction with the human instructor.

Based on data indicative of an area proximate to a robotic device, a scene is generated. Based on information from a knowledge database, a task associated with the scene is identified. A risk threshold is determined based on the scene, the task, and one or more trust thresholds. Based on the risk threshold, a ratio of sub-tasks of the task to be controlled by a user is determined. In accordance with the risk threshold, a user input is received for controlling one or more of the sub-tasks when the ratio dictates that at least one of the sub-tasks requires user intervention.

Provided is a multi-information provider system of a guidance robot and a method thereof. The multi-information provider system of a guidance robot may include a user database configured to receive and store user information transmitted from a terminal of a user, a robot database configured to receive pieces of robot information from one or more guidance robots and store the pieces of robot information, a valid robot list generator configured to list pieces of information of guidance robots located within a predetermined effective distance from a location of the user, a service matcher configured to match the user information and each of the pieces of robot information included in a valid robot list, and an outputter configured to output matched service information to the user terminal.

A robotic system includes a robot having a picking arm to grasp an inventory item and a shuttle. The shuttle includes a platform adapted to receive the inventory item from the picking arm of the robot. The platform is moveable between a pick-up location located substantially adjacent to the robot and an end location spaced a distance apart from the pick-up location. The system improves efficiency as transportation of the item from the pick-up location to the end location is divided between the robot and the shuttle.

A robot control device includes: a learned model created through learning work data composed of input and output data, the input data including states of a robot and the surroundings where humans operate the robot to perform a series of works, the output data including human operation corresponding to the case or movement of the robot caused thereby; a control data acquisition section that acquires control data by obtaining output data related to human operation or movement from the model, being presumed in response to and in accordance with the input data; a completion rate acquisition section acquiring a completion rate indicating to which progress level in the series of works the output data corresponds; and a certainty factor acquisition section that acquires a certainty factor indicating a probability of the presumption in a case where the model outputs the output data in response to the input data.

An autonomous moving body includes: a driven body including a carriage capable of moving autonomously; a battery; a first communication unit capable of communicating with a charging dock; and a first arithmetic processing unit for executing first arithmetic processing related to the drive of the driven body among arithmetic processings of the autonomous moving body. A charging dock includes: a charger for charging the battery; a second communication unit capable of communicating with the autonomous moving body; and a second arithmetic processing unit for executing second arithmetic processing other than the first arithmetic processing among the arithmetic processings of the autonomous moving body. The second communication unit is configured to be able to receive arithmetic data used for the second arithmetic processing from the first communication unit, and to transmit a processing result of the second arithmetic processing executed by the second arithmetic processing unit to the first communication unit.

A robot control system includes circuitry configured to: determine a necessity of assisting a robot to complete an automated work, based on environment information of the robot; select a remote operator from candidate remote operators based on stored operator data in response to determining that it is necessary to assist the robot to complete the automated work; transmit the environment information to the selected remote operator via a communication network; receive an operation instruction based on the environment information from the selected remote operator via the communication network; and control the robot to complete the automated work based on the operation instruction.

Implementations described herein relate to training and refining robotic control policies using imitation learning techniques. A robotic control policy can be initially trained based on human demonstrations of various robotic tasks. Further, the robotic control policy can be refined based on human interventions while a robot is performing a robotic task. In some implementations, the robotic control policy may determine whether the robot will fail in performance of the robotic task, and prompt a human to intervene in performance of the robotic task. In additional or alternative implementations, a representation of the sequence of actions can be visually rendered for presentation to the human can proactively intervene in performance of the robotic task.