A continuum arm robot system comprising at least a first continuum arm robot and a second continuum arm robot, each continuum arm robot being controlled by its own actuator pack, and each actuator pack being coupled to a single control computer, wherein at least the second continuum arm robot comprises a releasable connection mechanism to engage in gripping the first continuum arm robot in a workspace, so as to link the at least two continuum arm robots into a single redundant robotic system with at least the second continuum arm robot providing support for the first continuum arm robot.

Force and torque measurements from a robotic F/T sensor are compensated for the effects of gravity, and optionally additionally for the effects of robot motion. The weight of an attached tool W.sub.tool, and a vector {right arrow over (r)}.sub.CG from the F/T sensor body CF origin to a center of gravity of the tool are obtained, such as from user input or by parameter identification. During a robotic operation, a rotation matrix R.sub.International CF.sup.Body CF from the F/T sensor body CF to an inertial reference frame is obtained, such as from an internal inertial measurement unit (IMU), or from forward kinematics data from the robot. The force and torque measurements resolved by the F/T sensor from transducer outputs are compensated for gravity based on the W.sub.tool and {right arrow over (r)}.sub.CG, and the instantaneous value of R.sub.International CF.sup.Body CF. For inertial compensation, the additional information is obtained, including: the mass m of the attached tool; the angular velocity {right arrow over (ω)} of the F/T sensor body CF; the angular acceleration {dot over (ω)} of the F/T sensor body CF; the linear acceleration {right arrow over (a)} of the F/T sensor body CF; and inertia tensor I defined in the F/T sensor body CF which contains all moments and products of inertia. The force and torque measurements resolved by the F/T sensor from transducer outputs are compensated for inertial effects based on m, {right arrow over (ω)}, {right arrow over (ω)}, {right arrow over (r)}.sub.CG, {right arrow over (α)}, and I.

A gripping method relates to a method for gripping an object using a multi-fingered hand provided with a plurality of fingers. The method includes measuring, using a three-dimensional measurement sensor, an area that contains the object, and obtaining three-dimensional information for each position within the area, and deciding positions of the plurality of fingers for gripping the object, by classifying the area, if the area includes a measured area for which the three-dimensional information could be obtained and an unmeasured area for which the three-dimensional information could not be obtained, into the measured area and the unmeasured area based on the distance-indicating information, the positions of the plurality of fingers being decided based on positions of the unmeasured area.

A method for reducing vibration of a robot arm includes: a step of mounting at least one inertia actuator and at least one vibration signal capturing unit to a processing end of a robot arm; a step of applying the at least one vibration signal capturing unit to detect a vibration generated at the processing end of the robot arm so as to generate a vibration signal; a step of applying a central processing unit to evaluate the vibration signal and coordinates of the processing end of the robot arm so as to capture at least one set of corresponding control parameters for calculating at least one output force; and, a step of having the inertia actuator to apply the output force to the processing end of the robot arm for counteracting the vibration at the processing end of the robot arm.

A system and method for improving a position accuracy of a mobile robot is disclosed. A retroreflective device is mounted to the mobile robot and used by an absolute positioning device to use a laser beam to track a position of the mobile robot. The mobile robot receives position measurements. Various optimizations may be performed to support operating the mobile robot over a 360 degree range of azimuthal headings.

Generating a robot control policy that regulates both motion control and interaction with an environment and/or includes a learned potential function and/or dissipative field. Some implementations relate to resampling temporally distributed data points to generate spatially distributed data points, and generating the control policy using the spatially distributed data points. Some implementations additionally or alternatively relate to automatically determining a potential gradient for data points, and generating the control policy using the automatically determined potential gradient. Some implementations additionally or alternatively relate to determining and assigning a prior weight to each of the data points of multiple groups, and generating the control policy using the weights. Some implementations additionally or alternatively relate to defining and using non-uniform smoothness parameters at each data point, defining and using d parameters for stiffness and/or damping at each data point, and/or obviating the need to utilize virtual data points in generating the control policy.

A device for measuring repeated positioning precision of a robotic arm is introduced. Using an optical speckle three-dimensional displacement sensor developed by the inventor, and with collaboration of an optical speckle image three-dimensional positioning base built with an optical speckle coordinate database and having low thermal expansion, an optical speckle three-dimensional absolute positioning space is established. The optical speckle three-dimensional displacement sensor is installed on an end effector of a robotic arm, the robotic arm is moved to have the optical speckle three-dimensional displacement sensor enter an optical speckle three-dimensional absolute positioning space, an optical speckle image of a positioning point is captured and compared with a coordinate optical speckle image in the optical speckle coordinate database, and current three-dimensional absolute positioning coordinates of the end effector of the robotic arm can be obtained.

A coordinate positioning arm includes: a base end and a head end; a drive frame for moving the head end relative to the base end; and a metrology frame for measuring a position and orientation of the head end relative to the base end. The drive frame includes a plurality of drive axes arranged in series between the base end and the head end. The metrology frame includes a plurality of metrology axes arranged in series between the base end and the head end. The metrology frame is adapted and arranged to be substantially separate and/or independent from the drive frame, for example by supporting the metrology frame substantially only at the base end and head end and by providing the metrology frame with sufficient degrees of freedom (via the metrology axes) to avoid creating an additional constraint between the metrology frame and the drive frame.

An automated food production work cell includes a robotic system that utilizes a food-grade robotic gripper to transfer individual food items. The robotic gripper is constructed using food-grade materials and includes finger structures that are linearly movably connected by linear bearings to parallel guide rods and are independently driven by a non-contact actuating system to grasp targeted food items disposed on a first work surface, to hold the targeted food items while the robotic system moves the gripper to a second work surface, and to release the targeted food items onto the second work surface. Encoding and external sensing systems facilitate fully automated food transfer processes. Optional sensor arrays are disposed on tip portions of the finger structures to provide feedback data (e.g., grasping force/pressure). Two or more pairs of independently controlled finger structures are provided to facilitate the transfer of multiple food items during each transfer process.

In an embodiment, a method includes determining a given material to manipulate to achieve a goal state. The goal state can be one or more deformable or granular materials in a particular arrangement. The method further includes, for the given material, determining, a respective outcome for each of a plurality of candidate actions to manipulate the given material. The determining can be performed with a physics-based model, in one embodiment. The method further can include determining a given action of the candidate actions, where the outcome of the given action reaching the goal state is within at least one tolerance. The method further includes, based on a selected action of the given actions, generating a first motion plan for the selected action.