Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robotics planning. One of the methods comprises receiving data defining multiple skills to be performed by one or more robots in an operating environment; invoking a projection function implemented by each skill, wherein the projection function generates a skill footprint specifying resources requested for performing the skill and a volume occupied by a corresponding entity used to perform the skill; determining that the skill footprints generated by the projection functions are in conflict; and in response, executing the skills in sequence.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robotics planning. One of the methods comprises obtaining, for each of multiple skills to be performed by one or more robots in an operating environment, a skill footprint and a segmentation subset of the skill footprint that identifies one or more entities in the operating environment for performing the skill and that specifies requested permissions for the one or more entities; initiating execution of the skill; while the skill is executing, receiving a read or write request that references an entity that does not occur in the segmentation subset of the skill footprint; and in response, denying the read or write request that references the entity that does not occur in the segmentation subset of the skill footprint.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robotics planning. One of the methods comprises receiving data defining multiple skills to be performed by one or more robots in an operating environment; invoking a projection function implemented by a skill, wherein the projection function generates a skill footprint representing resources requested for performing the skill and a volume occupied by a corresponding entity used to perform the skill; determining that an initial skill footprint generated by the projection function conflicts with a skill footprint of another skill already being executed; and in response, reinvoking the projection function with data representing the skill footprint of the other skill already being executed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing robot planning using a process definition graph. One of the methods includes receiving an initial underconstrained process definition graph for one or more robots, wherein the process definition graph is a directed acyclic graph having constraint nodes and action nodes. A plurality of transformers are repeatedly applied to the initial process definition graph, wherein each application of a transformer generates a respective modified process definition graph according to the constraint nodes of the process definition graph, wherein applying the plurality of transformers generates a schedule that specifies which of the one or more robots are to perform which of one or more actions represented by actions nodes according to constraints imposed by the constraint nodes in the process definition graph.

Abstract: 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.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for planning by work volumes to avoid conflicts. One of the methods includes receiving a process definition graph for a robot that includes action nodes, wherein the action nodes include (1) transition nodes that represent a motion to be taken by the robot from a respective start location to an end location and (2) task nodes that represent a particular task to be performed by the robot at a particular task location. An initial modified process definition graph that ignores one or more conflicts between respective transition nodes as well as one or more conflicts between respective transition nodes and task nodes is generated from the process definition graph. A refined process definition graph that ignores conflicts between transition nodes and recognizes conflicts between transition nodes and task nodes is generated from the initial modified process definition graph.

Abstract: 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. One or more of the action nodes are motion nodes that represent a motion to be taken by the robot from a respective start location to an end location. It is determined that a motion node satisfies one or more splitting criteria, and in response to determining that the motion node satisfies the one or more splitting criteria, the process definition graph is modified. Modifying the process definition graph includes splitting the motion node into two or more separate motion nodes whose respective paths can be scheduled independently.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating motions for components in a robotic operating environment. One of the methods includes receiving a request to generate a motion for a kinematic system having a plurality of connected entities. An entity-specific sampling module for each of multiple degree-of-freedom (DOF) groups representing respective entities of the kinematic system is identified. A plurality of joint configuration samples are generated according to an ordering of a plurality of nonfunctional DOF groups using a respective entity-specific sampling module for each nonfunctional DOF group. A final joint configuration sample is generated for one or more one or more control points using a respective entity-specific sampling module for a functional DOF group. A motion comprising a sequence of respective joint configuration samples from each of the plurality of DOF groups is generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating motions for components in a robotic operating environment. One of the methods includes receiving a request to generate a motion for a kinematic system having a plurality of connected entities. An entity-specific sampling module for each of multiple degree-of-freedom (DOF) groups representing respective entities of the kinematic system is identified. A plurality of joint configuration samples are generated according to an ordering of a plurality of nonfunctional DOF groups using a respective entity-specific sampling module for each nonfunctional DOF group. A final joint configuration sample is generated for one or more one or more control points using a respective entity-specific sampling module for a functional DOF group. A motion comprising a sequence of respective joint configuration samples from each of the plurality of DOF groups is generated.

Abstract: Disclosed herein is a worksite automation process that involves: generating a first sequence of tasks to build the product according to a model. The process further involves causing one or more robotic devices to build the product by beginning to execute the first sequence of tasks. Further, during the execution of the first sequence of tasks, performing a buildability analysis to determine a feasibility of completing the product by executing the first sequence of tasks. Based on the analysis, determining that it is not feasible to complete the product by executing the first sequence of tasks, and in response, generating a second sequence of tasks to complete the product according to the model. Then, causing the one or more robotic devices to continue building the product by beginning to execute the second sequence of tasks.

Abstract: 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.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing robot fault recovery using a process definition graph. One of the methods includes receiving an indication that a robot experienced a fault while performing a schedule of commands generated from an original process definition graph, wherein the original process definition graph comprises a plurality of task nodes that represent a plurality of respective tasks to be performed by one or more robots. A recovery process definition graph is generated, wherein the recovery process definition graph includes a motion node that represents a motion action for the robot to take from a current position to a recovery position. On onsite execution engine executes the recovery process definition graph, thereby causing the robot to perform the motion action to move to the recovery position.

Abstract: 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. One or more of the action nodes are motion nodes that represent a motion to be taken by the robot from a respective start location to an end location. It is determined that a motion node satisfies one or more splitting criteria, and in response to determining that the motion node satisfies the one or more splitting criteria, the process definition graph is modified. Modifying the process definition graph includes splitting the motion node into two or more separate motion nodes whose respective paths can be scheduled independently.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing robot planning using a process definition graph. One of the methods includes receiving an initial underconstrained process definition graph for one or more robots, wherein the process definition graph is a directed acyclic graph having constraint nodes and action nodes. A plurality of transformers are repeatedly applied to the initial process definition graph, wherein each application of a transformer generates a respective modified process definition graph according to the constraint nodes of the process definition graph, wherein applying the plurality of transformers generates a schedule that specifies which of the one or more robots are to perform which of one or more actions represented by actions nodes according to constraints imposed by the constraint nodes in the process definition graph.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for planning by work volumes to avoid conflicts. One of the methods includes receiving a process definition graph for a robot that includes action nodes, wherein the action nodes include (1) transition nodes that represent a motion to be taken by the robot from a respective start location to an end location and (2) task nodes that represent a particular task to be performed by the robot at a particular task location. An initial modified process definition graph that ignores one or more conflicts between respective transition nodes as well as one or more conflicts between respective transition nodes and task nodes is generated from the process definition graph. A refined process definition graph that ignores conflicts between transition nodes and recognizes conflicts between transition nodes and task nodes is generated from the initial modified process definition graph.

Abstract: Disclosed herein is a worksite automation process that involves: generating a first sequence of tasks to build the product according to a model. The process further involves causing one or more robotic devices to build the product by beginning to execute the first sequence of tasks. Further, during the execution of the first sequence of tasks, performing a buildability analysis to determine a feasibility of completing the product by executing the first sequence of tasks. Based on the analysis, determining that it is not feasible to complete the product by executing the first sequence of tasks, and in response, generating a second sequence of tasks to complete the product according to the model. Then, causing the one or more robotic devices to continue building the product by beginning to execute the second sequence of tasks.

Abstract: Disclosed herein is a worksite automation process that involves: generating a first sequence of tasks to build the product according to a model. The process further involves causing one or more robotic devices to build the product by beginning to execute the first sequence of tasks. Further, during the execution of the first sequence of tasks, performing a buildability analysis to determine a feasibility of completing the product by executing the first sequence of tasks. Based on the analysis, determining that it is not feasible to complete the product by executing the first sequence of tasks, and in response, generating a second sequence of tasks to complete the product according to the model. Then, causing the one or more robotic devices to continue building the product by beginning to execute the second sequence of tasks.