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.

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.

Systems and a method for determining a sequence of kinematic chains of a multiple robot along a sequence of locations. Inputs on the locations to be reached by a robot tool are received. Each chain is considered separately by setting one chain in use and determining, for each chain in use, available configurations for each location. The available configurations are represented as nodes of a graph representing available robotic paths for reaching with a tool the locations, while allowing the switching among different chains within the same robotic path. Valid connectors are determined by simulating collision free robot trajectories while taking into account working modality constraints of the locations. Weight factors are assigned to connectors to represent robot efforts in moving between subsequent configurations. The shortest robotic path among valid paths is determined by taking into account the weight factors. The sequence of chains is determined from the shortest path.

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.

Systems and a method for determining a sequence of kinematic chains of a multiple robot along a sequence of locations. Inputs on the locations to be reached by a robot tool are received. Each chain is considered separately by setting one chain in use and determining, for each chain in use, available configurations for each location. The available configurations are represented as nodes of a graph representing available robotic paths for reaching with a tool the locations, while allowing the switching among different chains within the same robotic path. Valid connectors are determined by simulating collision free robot trajectories while taking into account working modality constraints of the locations. Weight factors are assigned to connectors to represent robot efforts in moving between subsequent configurations. The shortest robotic path among valid paths is determined by taking into account the weight factors. The sequence of chains is determined from the shortest path.

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.

Systems and methods are provided that introduce an improved way of producing fast and optimal motion plans by using Recurrent Neural Networks (RNN) to determine end-to-end trajectories in an iterative manner. By using an RNN in this way and offloading expensive computation towards offline learning, a network is developed that implicitly generates optimal motion plans with minimal loss in performance in a compact form. This method generates near optimal paths in a single, iterative, end-to-end roll-out that that has effectively fixed-time execution regardless of the configuration space complexity. Thus, the method results in fast, consistent, and optimal trajectories that outperform popular motion planning strategies in generating motion plans.

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.