A system for assembling a vehicle platform includes a robotic assembly system having at least two robotic arms, a vision system capturing images of an assembly frame, and a control system configured to control the robotic assembly system to assemble the vehicle platform based on images from the vision system, force feedback from the at least two robotic arms, and a component location model. The control system is further configured to identify assembly features of a first component and a second component of the vehicle platform from the images, operate the robotic arms to orient the first component and the second component to respective nominal positions based on the images and the component location model, and operate the robotic arms to assemble the first component to the second component based on the force feedback.

A dual-manipulator control method is configured to be used in a dual-manipulator control system including a first manipulator, a second manipulator, and a central control module. The first manipulator and the second manipulator are controlled by the central control module, and the central control module is configured to execute the dual-manipulator control method. The dual-manipulator control method includes: generating a first instruction sequence to control the first manipulator and a second instruction sequence to control the second manipulator; and controlling the first manipulator and the second manipulator based on the first instruction sequence and the second instruction sequence. Thus, the working efficiency is improved.

A system for assembling a vehicle platform includes a robotic assembly system having at least two robotic arms, a vision system capturing images of an assembly frame, and a control system configured to control the robotic assembly system to assemble the vehicle platform based on images from the vision system, force feedback from the at least two robotic arms, and a component location model. The control system is further configured to identify assembly features of a first component and a second component of the vehicle platform from the images, operate the robotic arms to orient the first component and the second component to respective nominal positions based on the images and the component location model, and operate the robotic arms to assemble the first component to the second component based on the force feedback.

A control apparatus is a control apparatus that controls a first manipulator including a detection acquisition unit that acquires information from a first detection unit detecting that at least one of a living organism and an object is located within a first range, a velocity acquisition unit that acquires a velocity of a second manipulator different from the first manipulator, and a control unit that controls a velocity of the first manipulator to be equal to or less than a first velocity, wherein the control unit controls the velocity of the first manipulator so that a relative velocity between the first manipulator and the second manipulator may be equal to or less than a second velocity when the detection acquisition unit acquires the information.

A multi-scale inspection and intelligent diagnosis system and method for tunnel structural defects includes: a traveling section; a supporting section, disposed on the traveling section, and including a rotatable telescopic platform, where two mechanical arms working in parallel are disposed on the rotatable telescopic platform; an inspection section, mounted on the supporting section, and configured to perform multi-scale inspection on surface defects and internal defects in different depth ranges of a same position of a tunnel structure, and transmit inspected defect information to a control section; and the control section, configured to: construct a deep neural network-based defect diagnosis model; construct a data set by using historical surface defect and internal defect information, and train the deep neural network-based defect diagnosis model; and receive multi-scale inspection information in real time, and automatically recognize types, positions, contours, and dielectric attributes of the internal and surface defects.

A method and system for controlling at least one effector trajectory for at least one effector of a robot for solving a predefined task are proposed. A graph of postures is acquired, and at least one of a contact constraint topology and an object constraint topology are accordingly modified. A set of constraint equations based on at least one of the modified contact constraint topology and the modified object constraint topology are generated. Constraint relaxation is performed on the generated set of constraint equations to generate a task description including the relaxed set of constraint equations. The effector trajectory is generated by applying a trajectory generation algorithm on the generated task description. An inverse kinematics algorithm is performed on the generated effector trajectory for generating a control signal, and the effector is controlled to execute the effector trajectory based on the generated control signal.

A method and simulation system for controlling at least one effector trajectory for solving a predefined task by at least one virtual effector. The method includes acquiring a sequence of postures to modify at least one of a contact constraint topology and an object constraint topology, generating a set of constraint equations based on at least one of the modified contact constraint topology and the modified object constraint topology, performing constraint relaxation on the generated set of constraint equations to generate a task description including the relaxed set of constraint equations, generating the effector trajectory by applying a trajectory generation algorithm on the generated task description, performing an inverse kinematics algorithm on the generated effector trajectory for generating a control signal, outputting the control signal to an output device, and generating, by the output device, image information displaying the effector trajectory of the virtual effector based on the control signal.

A method and simulation system for controlling at least one effector trajectory for solving a predefined task by at least one virtual effector. The method includes acquiring a sequence of postures to modify at least one of a contact constraint topology and an object constraint topology, generating a set of constraint equations based on at least one of the modified contact constraint topology and the modified object constraint topology, performing constraint relaxation on the generated set of constraint equations to generate a task description including the relaxed set of constraint equations, generating the effector trajectory by applying a trajectory generation algorithm on the generated task description, performing an inverse kinematics algorithm on the generated effector trajectory for generating a control signal, outputting the control signal to an output device, and generating, by the output device, image information displaying the effector trajectory of the virtual effector based on the control signal.

A method and system for controlling at least one effector trajectory for at least one effector of a robot for solving a predefined task are proposed. A graph of postures is acquired, and at least one of a contact constraint topology and an object constraint topology are accordingly modified. A set of constraint equations based on at least one of the modified contact constraint topology and the modified object constraint topology are generated. Constraint relaxation is performed on the generated set of constraint equations to generate a task description including the relaxed set of constraint equations. The effector trajectory is generated by applying a trajectory generation algorithm on the generated task description. An inverse kinematics algorithm is performed on the generated effector trajectory for generating a control signal, and the effector is controlled to execute the effector trajectory based on the generated control signal.

There is provided a data processing device and a data processing method capable of improving reproducibility in a case where a cooking robot reproduces the same dish as a dish cooked by a cook. The data processing device according to one aspect of the present technology generates recipe data including a data set used when a cooking robot performs a cooking operation, the data set linking cooking operation data in which information regarding an ingredient of a dish and information regarding an operation of a cook in a cooking process using the ingredient are described, and sensation data indicating a sensation of the cook measured in conjunction with progress of the cooking process. The present technology can be applied to a computer that controls cooking in a cooking robot.