In the following, a method for synchronizing the motion sequences of at least two robots will be described. In accordance with one embodiment, the method comprises the following: During operation of a robot cell having at least two robots, a path parameter is regularly calculated for each of the at least two robots based on a current position of the respective robot and on a previously specified robot path of the respective robot. The path parameter represents the current position of the robot. Subsequently, a run-ahead limit is calculated for each robot based on the path parameters determined for the respective other robots. Based on the respective calculated run-ahead limit, the path speed of every robot can be adjusted.

The present disclosure relates to a method for generating a novel impedance configuration for a three-degree-of-freedom (3DOF) leg of a hydraulically-driven legged robot. The method includes: separately determining variations of input signals of an inner position-based control loop and an inner force-based control loop of a hydraulic drive unit of each joint based on an obtained mathematical model; generating a novel impedance configuration in which position-based control is performed on a hydraulic drive unit of a hip joint, and force-based control is performed on hydraulic drive units of a knee joint and an ankle joint in a hydraulic drive system of the leg of a to-be-controlled robot; and performing forward calculation by using the leg mathematical model, to obtain an actual position and a force variation of the foot of the leg of the to-be-controlled robot to control motion of the foot of the to-be-controlled robot within motion space.

An end-effector may include a base, a plurality of underactuated fingers coupled to the base; and an adhesion gripper coupled to the base. An end-effector may include a base, an actuator, a first underactuated finger comprising a proximal link and a distal link, the proximal link including a distal end, a guide for a first tendon spaced a first distance away from the distal end of the proximal link and the distal link including a lever arm disposed on a proximal side to the distal pad and which extends in a volar direction from a first axis, and a node disposed on the lever arm sized and shaped to receive a first tendon. The end-effector may include a first revolute joint compliant in a first direction disposed between the base and the proximal link; and a second revolute joint compliant in the first direction disposed between the proximal link and the distal link.

The present application discloses a system, a method, and a computer system for moving items deemed to be too heavy to be picked up by a robotic arm. The method includes (i) receiving image data associated with a workspace, wherein the workspace includes a source of items to be placed singly each in a respective corresponding location on a segmented conveyance structure adjacent to at least a portion of the source of items, (ii) receiving an indication that a first item in the source of items is too heavy to be picked up by a first robotic arm the one or more processors are configured to control, (iii) determining, based at least in part on the image data, a plan to use the first robotic arm to push the first item onto an associated corresponding location on the segmented conveyance structure as the associated corresponding location on the segmented conveyance structure moves past the source of items, and (iv) controlling the first robotic arm to implement the plan.

Disclosed is a moving robot capable of recognizing a waiting line and a method for controlling the same. One embodiment provides a method for operating a moving robot, the method comprising: starting moving from a predefined moving start point toward a predefined moving end point; acquiring a waiting line region image by photographing a predefined waiting line region during the moving; searching for an end point of a waiting line formed in the waiting line region using the waiting line region image; terminating the moving when the end point of the waiting line is detected; setting an operation mode based on a length of the waiting line calculated using the end point of the waiting line; and operating in the set operation mode while returning to the moving start point.

A manipulation controller is provided for reorienting an object by a manipulator of a robotic system. The manipulation controller includes an interface controller configured to acquire measurement data from sensors arranged on the robotic system, at least one processor, and a memory configured to store a computer-implemented method. The instructions of the method include acquiring measurement data from vision sensors and force sensors arranged on the robotic system, determining an input-output relation for the object based on a nonlinear static model representing input-output relationships between contact forces and movements of the object on the workbench, representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator, formulating a representation for frictional stability of the object based on the non-linear static model at the external contacts with the workbench; formulating a bilevel optimization problem so as to maximize the frictional stability over a position trajectory of the object being manipulated on the workbench, estimating uncertainty value in physical parameters to be compensated by performing the bilevel optimization problem, solving the bilevel optimization problem using the non-linear optimization solver and generating control data with respect to a sequence of the contact forces being applied to the object by using the manipulator.

It is an object to enable a grasping operation to be executed according to a state of an object. The invention provides an information processing apparatus which determines the grasping operation in a grasping unit for grasping the object. The information processing apparatus has: an obtaining unit for obtaining an image acquired by capturing the object; a recognizing unit for recognizing a state of the object from the image obtained by the obtaining unit; and a generating unit for generating information for allowing the grasping unit to execute the grasping operation on the basis of the object state recognized by the recognizing unit and conditions to execute the grasping operation.

Techniques for fingertip design are disclosed that leverage how most grasp contacts can share a few classes of local geometries. In order to maximize the contact areas for achieving more robust grasps, contact primitives, which represent a set of contacts of similar local geometries, are identified. A uniform cost algorithm, which can be formulated as a decision making process in a tree structure, can be utilized to cluster a set of example grasp contacts into a finite set of one or more contact primitives. Fingertips can be designed by optimization to match the local geometry of each contact primitive, and then fingertips can be 3D printed using soft materials to compensate for optimization residuals. For novel objects, an approach to generate grasp contacts that match the fingertip geometries while together forming stable grasps can be utilized.

A method for robot control using visual feedback including determining a generative model S100, training the generative model S200, and controlling the robot using the trained generative model S300.

An arrangement for handling objects on an object transporting device includes an industrial robot and an object handling control device. The device estimates candidate handling positions (OP1, OP2, OP3, OP4, OP5, OP6, OP7) for at least one candidate object based on a first assumption; determines for each candidate handling position whether it lies within a working volume (wv1) of the robot; selects one of the candidate positions (OP1) at a first decision instant, the selection being at least partially based on the result of the determining; and handles an object at an actual handling position corresponding to the selected candidate handling position, the handling being performed after a usage time of the robot, the usage time including the time for moving the robot from the robot position at the first decision instant to the actual handling position, and the time for handling the object.