Fanuc Corporation

Hsien-Chung Lin

Tetsuaki Kato

Yongxiang Fan

Chiara Talignani Landi

Chi-Keng Tsai

Yu Zhao

Changhao Wang

A robot interference checking motion planning technique using point sets. The technique uses CAD models of robot arms and obstacles and converts the CAD models to 3D point sets. The 3D point set coordinates are updated at each time step based on robot and obstacle motion. The 3D points are then converted to 3D grid space indices indicating space occupied by any point on any part. The 3D grid space indices are converted to 1D indices and the 1D indices are stored as sets per object and per time step. Interference checking is performed by computing an intersection of the 1D index sets for a given time step. Swept volumes are created by computing a union of the 1D index sets across multiple time steps. The 1D indices are converted back to 3D coordinates to define the 3D shapes of the swept volumes and the 3D locations of any interferences.

Point set interference check method and system

A method and system for robotic motion planning which perform dynamic velocity attenuation to avoid robot collision with static or dynamic objects. The technique maintains the planned robot tool path even when speed reduction is necessary, by providing feedback of a computed slowdown ratio to a tracking controller so that the path computation is always synchronized with current robot speed. The technique uses both robot-obstacle distance and relative velocity to determine when to apply velocity attenuation, and computes a joint speed limit vector based on a robot-obstacle distance, a maximum obstacle speed, and a computed stopping time as a function of the joint speed. Two different control structure implementations are disclosed, both of which provide feedback of the slowdown ratio to the motion planner as needed for faithful path following. A method of establishing velocity attenuation priority in multi-robot systems is also provided.

Method of robotic system dynamic velocity modification

A method and system for motion planning for robots with a redundant degree of freedom. The technique computes a collision avoidance motion plan for a robot with a redundant degree of freedom, without artificially constraining the extra degree of freedom. The motion planning is formulated as a quadratic programming optimization calculation having a multi-component objective function and a collision avoidance constraint function. The formulation is efficient enough to compute the motion plan in real time at every robot control cycle. The collision avoidance constraint ensures clearance of all parts of the robot from both static and dynamic obstacles. Objective function terms include minimizing path deviation, joint velocity regularization and robot configuration or pose regularization. Weighting factors on the terms of the objective function are changeable for each control cycle calculation based on obstacle proximity conditions at the time.

Method of robot dynamic motion planning and control

A robot motion planning technique using an external computer communicating with a robot controller. A camera or sensor system provides input scene information including start and goal points and obstacle data to the computer. The computer plans a robot tool motion based on the start and goal points and the obstacle environment, where the robot motion is planned using either a serial or parallel combination of sampling-based and optimization-based planning algorithms. In the serial combination, the sampling method first finds a feasible path, and the optimization method then improves the path quality. In the parallel combination, both sampling and optimization methods are used, and a path is selected based on computation time, path quality and other factors. The computer converts dense planned waypoints to sparse command points for transfer to the robot controller, and the controller computes robot kinematics and interpolation points and controls the movement of the robot.

Framework of robotic online motion planning

A robot interference checking motion planning technique using swept volume deformation. A rapidly-exploring random tree (RRT) algorithm generates random sample nodes between a start point and a goal point. Each sample node is evaluated by checking for robot-obstacle interference along a path segment to the node. If an interference exists along the path segment, a swept volume of the segment is used to identify a critical posture where the interference is greatest, and obstacle interference points are used to define a virtual force applied to the robot links to modify the path segment to alleviate the interference condition. A swept volume of the modified path segment is computed and evaluated. If the modified swept volume is collision-free and the modified path segment motion plan meets robot joint range criteria, the modified path segment and the sample node are added to the overall robot motion program.

Swept volume deformation

A method and system for robot motion control using a model predictive control (MPC) technique including torque rate control and suppression of end tooling oscillation. An MPC module includes a robot dynamics model which inherently reflects response nonlinearities associated with changes in robot configuration, and an optimization solver having an objective function with a torque rate term and inequality constraints defining bounds on both torque and torque rate. The torque rate control in the MPC module provides an effective means of controlling jerk in robot joints, while accurately modeling robot dynamics as the robot changes configuration during a motion program. End tooling oscillation dynamics may also be included in the MPC objective function and constraints in order to automatically control end tooling vibration in the calculations of the MPC module.

Predictive control method for torque-rate control and vibration suppression

A method and system for calculating a minimum distance from a robot to dynamic objects in a robot workspace. The method uses images from one or more three-dimensional cameras, where edges of objects are detected in each image, and the robot and the background are subtracted from the resultant image, leaving only object edge pixels. Depth values are then overlaid on the object edge pixels, and distance calculations are performed only between the edge pixels and control points on the robot arms. Two or more cameras may be used to resolve object occlusion, where each camera's minimum distance is computed independently and the maximum of the cameras' minimum distances is used as the actual result. The use of multiple cameras does not significantly increase computational load, and does require calibration of the cameras with respect to each other.

Effective calculation method of the minimum distance to dynamic objects

A robotic grasp generation technique for part picking applications. Part and gripper geometry are provided as inputs, typically from CAD files. Gripper kinematics are also defined as an input. A set of candidate grasps is provided using any known preliminary grasp generation tool. A point model of the part and a model of the gripper contact surfaces with a clearance margin are used in an optimization computation applied to each of the candidate grasps, resulting in an adjusted grasp database. The adjusted grasps optimize grasp quality using a virtual gripper surface, which positions the actual gripper surface a small distance away from the part. A signed distance field calculation is then performed on each of the adjusted grasps, and those with any collision between the gripper and the part are discarded. The resulting grasp database includes high quality collision-free grasps for use in a robotic part pick-and-place operation.

Collision handling methods in grasp generation

Point set interference check

A method and system for dynamic collision avoidance motion planning for industrial robots. An obstacle avoidance motion optimization routine receives a planned path and obstacle detection data as inputs, and computes a commanded robot path which avoids any detected obstacles. Robot joint motions to follow the tool center point path are used by a robot controller to command robot motion. The planning and optimization calculations are performed in a feedback loop which is decoupled from the controller feedback loop which computes robot commands based on actual robot position. The two feedback loops perform planning, command and control calculations in real time, including responding to dynamic obstacles which may be present in the robot workspace. The optimization calculations include a safety function which efficiently incorporates both relative position and relative velocity of the obstacles with respect to the robot.

Dynamic motion planning system

A robot collision avoidance motion planning technique using a worst state search and optimization. The motion planning technique begins with a geometric definition of obstacles, start and goal points, and an initial set of waypoints which may be sparsely spaced. Given an inter-point interpolation method such as linear or spline, a continuous trajectory can be described as a function of the waypoints and an arc length parameter. A worst state search is then performed which finds a location between each adjacent pair of waypoints having a worst state of distance to obstacle, considering all parts of the robot and tool. A collision avoidance constraint is defined using the worst state locations, and an optimization of the waypoint locations is then performed to improve the worst states until all collisions are eliminated and an obstacle avoidance minimum distance criteria is met.

Collision avoidance motion planning method for industrial robot

A robot collision avoidance motion optimization technique using a distance field constraint function. CAD or sensor data depicting obstacles in a robot workspace are converted to voxels, and a three-dimensional binary matrix of voxel occupancy is created. A corresponding distance map matrix is then computed, where each cell in the distance map matrix contains a distance to a nearest occupied cell. The distance map matrix is used as a constraint function in a motion planning optimization problem, where the optimization problem is convexified and then iteratively solved to yield a robot motion profile which avoids the obstacles and minimizes an objective function such as distance traveled. The distance field optimization technique is quickly computed and has a computation time which is independent of the number of obstacles. The disclosed optimization technique is easy to set up, as it requires no creation of geometry primitives to approximate robot and obstacle shapes.

Fast robot motion optimization with distance field

A robot optimization motion planning technique using a refined initial reference path. When a new path is to be computed using motion optimization, a candidate reference path is selected from storage which was previously computed and which has similar start and goal points and collision avoidance environment constraints to the new path. The candidate reference path is adjusted at all state points along its length to account for the difference between the start and goal points of the new path compared to those of the previously-computed path, to create the initial reference path. The initial reference path, adjusted to fit the start and goal points, is then used as a starting state for the motion optimization computation. By using an initial reference path which is similar to the final converged new path, the optimization computation converges more quickly than if a na&#xef;ve initial reference path is used.

Initial reference generation for robot optimization motion planning

A state machine controller to dynamically plan a robot's path. An industrial robot such as a multi-arm articulated robot operates in a workspace according to a program. A sensor or camera monitors the workspace and detects any object, such as a person, approaching or entering the workspace. The sensor provides input to the state machine controller, which includes states of; track current path, change speed, and replan path. When an object approaches or enters the workspace, the state machine determines if a transition to the change speed state is necessary. After reducing robot speed in the change speed state, the state machine can resume the original path and speed if the object has cleared the workspace, further reduce speed to zero if necessary to avoid a collision, or transition to the replan path state to compute a new path to the goal position which avoids the object in the workspace.

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Fremont, CA, United States of America

Hsien-Chung Lin