In one embodiment, a method is provided. The method includes obtaining sensor data indicative of a set of objects detected within an environment. The method also includes determining a set of positions of the set of objects and a set of properties of the set of objects based on the sensor data. The method further includes generating a state graph based on the sensor data. The state graph represents the set of objects and the set of positions of the set of objects. The state graph includes a set of object nodes to represent the set of objects and a set of property nodes to represent the set of properties of the set of objects. The state graph is provided to a graph enhancement module that updates the state graph with additional data to generate an enhanced state graph.

A method is provided. The method includes obtaining a state graph that represents a set of objects within an environment and a set of positions of the set of objects within the environment. The state graph includes a set of object nodes and a set of property nodes. The method also includes obtaining user input data. The user input data is generated based on a natural language input. The method further includes updating the state graph based on the user input data to generate an enhanced state graph. The enhanced state graph includes additional nodes generated based on the user input data. The method further includes providing the enhanced state graph to a planning module. The planning modules generates instructions for operating a mechanical system based on the enhanced state graph.

A method is provided. The method includes obtaining sensor data indicative of a set of objects detected within an environment. The method also includes generating a state graph based on the sensor data. The state graph includes a set of object nodes and a set of property nodes. The method further includes obtaining user input data generated based on a natural language input. The method further includes updating the state graph based on the user input data to generate an enhanced state graph. The enhanced state graph includes additional nodes generated based on the user input data. The method further includes generating a set of instructions for a set of mechanical systems based on the enhanced state graph. The method further includes operating the set of mechanical systems to achieve a set of objectives based on the set of instructions.

An apparatus for generating multiple paths for a mobile robot includes a multi-path generation module that detects “n” multiple waypoints located at a maximum straight line distance without collision with an obstacle in a space within a predetermined radius in “n” directions centered on the mobile robot, and plans “n” multiple paths to a destination by passing through each of the multiple waypoints as an initial waypoint, and an optimal path selection module that selects a path satisfying a preset cost function requirement among the “n” multiple paths, which are planned, as an optimal path, making it possible to select the optimal path suitable for various driving situations of the mobile robot by simultaneously generating multiple paths along which the mobile robot is to travel from its current location to its destination.

A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change.

Methods, systems, and platforms for automatic setup planning for a robot. The method includes sampling multiple poses in multiple dimensions within a robotic workspace. The method includes generating one or more candidate configurations based on the multiple poses. The method includes determining a score for each candidate configuration of the one or more candidate configurations. The score represents area coverage of a region of interest and at least one of an amount of setup time of the candidate configuration or an amount of energy used. The method includes determining a set of candidate configurations that has an overall area coverage that covers the region of interest based on the score for each candidate configuration. The method includes controlling a position and an orientation of the object based on the set of candidate configurations.

Methods, systems, and apparatus for automatically moving a tool attached to a robotic manipulator from a start position to a goal position. The method includes determining, using a processor, a plurality of next possible positions from the start position. The method includes selecting a second position from the plurality of next possible positions based on respective costs associated with moving the tool from the start position to each of the possible positions in the plurality of next possible positions. The method includes moving, using a plurality of actuators, the tool to the second position. The method includes determining an updated plurality of next possible positions, selecting a next position, and moving the tool to the next position until the goal position is reached.

The present disclosure proposes a method and an apparatus for generating an action sequence of a robot. The method includes: obtaining a directed graph, in which the directed graph comprises a plurality of nodes for instructing actions of the robot, and directed edges connecting the nodes; obtaining target actions involved in a task, and an execution order of the target actions; in the directed graph, performing a search in directions indicated by the directed edges to obtain a target path, in which nodes on the target path comprises target nodes corresponding to the target actions, and an order of the target path passing through the target nodes matches an execution order of the target actions; and generating the action sequence of the robot according to actions instructed by the target path and an execution order of the actions instructed by the target path.

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.

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 a schedule generated for actions represented in a process definition graph for one or more robots, wherein the process definition graph is a directed acyclic graph having constraint nodes and action nodes. User input selecting a particular modification to be applied to the process definition graph is received, and the user-selected modification is applied to generate a modified process definition graph.