The embodiments of present disclosure herein address unresolved problem of cognitive navigation strategies for a telepresence robotic system. This includes giving instruction remotely over network to go to a point in an indoor space, to go an area, to go to an object. Also, human robot interaction to give and understand interaction is not integrated in a common telepresence framework. The embodiments herein provide a telepresence robotic system empowered with a smart navigation which is based on in situ intelligent visual semantic mapping of the live scene captured by a robot. It further presents an edge-centric software architecture of a teledrive comprising a speech recognition based HRI, a navigation module and a real-time WebRTC based communication framework that holds the entire telepresence robotic system together. Additionally, the disclosure provides a robot independent API calls via device driver ROS, making the offering hardware independent and capable of running in any robot.

A program creation apparatus acquires a work sequence executed by a robot, and creates a motion program based on the work sequence and a work information file in which information on work contained in the work sequence is recorded. Further, the work sequence is corrected from the work information file, and a new motion program based on a corrected new work sequence is created.

Robots are deployed for handling different tasks in various field of applications. For the robots to function, task planning is required to be done. During the task planning, goal setting is done, as well as actions to be executed for corresponding to each goal are decided. Traditionally, this is carried out first and then the robots start executing the task plan, thereby failing to capture any change in the environment the robots operate, post the task plan generation. Disclosed herein is a method and system for robotic task planning in which a task plan is generated and is executed. However if the task execution fails due to change in any of the parameters/factors, then the system dynamically invokes an adaptation and re-planning mechanism which either updates the already generated task plan (by capturing the change) or generates a new task plan, which the robot can execute to achieve the goal.

Methods, systems, and computer programs stored on computer storage devices, for coordinating movements of robots are disclosed. One of the methods includes, for each robot in a group of robots, identifying a set of tasks assigned to the robot and generating a plurality of candidate motion plans. The method further includes, for each candidate motion plan: (i) generating a 3D model that represents a volume of space through which the robot would move in executing the sequence of motions represented by the candidate motion plan, and (ii) determining a score for the candidate motion plan. The method further includes determining conflicts between candidate motion plans of different robots, selecting a motion plan from the candidate motion plans based on the score for the selected motion plan and the conflicts, and providing the selected motion plans for execution by the group of robots.

Robotic task program synthesis embodiments are presented that generally synthesize a robotic task program based on received examples of repositioning tasks. In one implementation, the exemplary repositioning tasks are human demonstrations of object manipulation in an actual or displayed robot workspace. A domain specific language (DSL) designed for object repositioning tasks is employed for the robotic control program. In general, candidate robotic task programs are generated from the example tasks. Each candidate program includes instructions for causing the robot to reposition objects, and represents a different permutation of instructions consistent with the received example tasks. The candidate programs are ranked, and whenever the top ranking program accomplishes the repositioning specified in each example task, it is designated as the synthesized robotic task program.

A method of generating a building assembly that includes spraying a coating material onto a plurality of pieces of substrate disposed on a first assembly face. The spraying includes spraying the coating material onto the plurality of pieces of substrate via a sprayer configured to apply the coating material to a target surface via a nozzle coupled with a mobile storage container storing the coating material, the coating material impregnating voids of the substrate. The method also includes allowing the coating material impregnating the voids to dry and harden and become rigid to generate the building assembly.

Methods, systems, and computer programs stored on computer storage devices, for coordinating movements of robots are disclosed. One of the methods includes, for each robot in a group of robots, identifying a set of tasks assigned to the robot and generating a plurality of candidate motion plans. The method further includes, for each candidate motion plan: (i) generating a 3D model that represents a volume of space through which the robot would move in executing the sequence of motions represented by the candidate motion plan, and (ii) determining a score for the candidate motion plan. The method further includes determining conflicts between candidate motion plans of different robots, selecting a motion plan from the candidate motion plans based on the score for the selected motion plan and the conflicts, and providing the selected motion plans for execution by the group of robots.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a system for decentralized and validated robotic planning. One of the methods includes obtaining data representing an optimization challenge for a task to be performed by one or more robots in a robotic operating environment, wherein the optimization challenge has one or more associated goal criteria for the task; providing, by the validation platform system to a development platform system operated by a different entity than the validation platform system, information related to the optimization challenge; obtaining a candidate robotic control plan; executing the candidate robotic control plan using the digital representation of the robotic operating environment; determining that the candidate robotic control plan is valid according to the one or more goal criteria; and in response, providing the valid robotic control plan for deployment in the robotic operating environment.

Methods, systems, and computer programs stored on computer storage devices, for coordinating movements of robots are disclosed. One of the methods includes, for each robot in a group of robots, identifying a set of tasks assigned to the robot and generating a plurality of candidate motion plans. The method further includes, for each candidate motion plan: (i) generating a 3D model that represents a volume of space through which the robot would move in executing the sequence of motions represented by the candidate motion plan, and (ii) determining a score for the candidate motion plan. The method further includes determining conflicts between candidate motion plans of different robots, selecting a motion plan from the candidate motion plans based on the score for the selected motion plan and the conflicts, and providing the selected motion plans for execution by the group of robots.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing a plan for one or more robots using a process definition graph. One of the methods includes receiving a process definition graph for a robot, the process definition graph having a plurality of action nodes, and the plurality of action nodes including a plurality of motion nodes that were previously split from a single motion node due to a conflict with a second motion node representing a second motion to be performed by another robot; determining that the conflict with the second motion node no longer exists; and in response to determining that the conflict with the second motion node no longer exists, modifying the process definition graph including combining the plurality of motion nodes into a new single motion node representing all of the motions of the plurality of motion nodes.