Specialized robot motion planning hardware and methods of making and using same are provided. A robot-specific hardware can be designed using a tool that receives a robot description comprising a collision geometry of a robot, degrees of freedom for each joint of the robot, and joint limits of the robot; receives a scenario description; generates a probabilistic roadmap (PRM) using the robot description and the scenario description; and for each edge of PRM, produces a collision detection unit comprising a circuit indicating all parts of obstacles that collide with that edge. The hardware is implemented as parallel collision detection units that provide collision detection results used to remove edges from the PRM that is searched to find a path to a goal position.

A method and computing system comprising identifying a plurality of robot configurations for each inspection point of a plurality of inspection points of a problem. A graph may be generated with each feasible robot configuration as a node on the graph. A distance may be calculated between a pair of feasible robot configurations. A shortest complete path connecting each node on the graph may be obtained based upon, at least in part, the distance between the pair of feasible robot configurations.

Methods, apparatus, systems, and computer-readable media are provided for training a path of a robot within a graphical user interface (GUI) and/or by physically moving the robot. In particular, the technology generates a trained path for the robot based on waypoints defined by a user and generates one or more parameters for one or more movement characteristics of the robot along the trained path. The parameters for the movement characteristics are generated based on spatial proximity of a plurality of the waypoints that are defined by the user.

The present invention relates to a collision-free path generating method for a robot and an end effector quipped thereon to move. The method includes steps of configuring a virtual working environment, containing a plurality of virtual objects at least including the robot, the end effector and a target object consisting of a plurality of basic members and mapped from a working environment in a reality, in a robot simulator; selecting a level of detail and a pre-determined shape for a collider covering the plurality of virtual objects to determine boundaries for the plurality of objects; randomly sampling a combination of robot configurations; and based on the determine boundaries and the randomly sampled combination of robot configurations, performing a heuristic based pathfinding algorithm to compute a collision-free path for the robot and the end effector quipped thereon to move to the target object accordingly.

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.

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.

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 apparatus, including computer programs encoded on computer storage media, for generating paths for a robot based on optimizing multiple objectives. One of the methods includes: receiving, by a motion planner, request to generate a path for a robot between a start point and an end point in a workcell of the robot, wherein the workcell is associated with one or more soft margin values that define spaces in which the robot should avoid when transitioning between points in the workcell; classifying path segments within the workcell as being inside the soft margin or outside the soft margin; generating a respective cost for each of the plurality of path segments within the workcell; generating a plurality of alternative paths; evaluating the plurality of alternative paths according to the respective costs; and selecting an alternative path based on respective total costs of the plurality of alternative paths.

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.

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.