An automated continuous or near-continuous system for sorting and combining varying density payloads comprises a buffer area including a work surface having a plurality of holes for storing a plurality of cups with weighed payloads, a shuttle, and scale system configured for weighing and near continuously or continuously delivering the plurality of cups with the payloads, to the buffer area, at least one robot provided within the buffer area, wherein the at least one robot is configured for picking a cup carrying a payload, from either one of the shuttle and scale system and the work surface, and transporting the payload from the cup into an accumulator. The at least one robot is configured for delivering one or more of the payloads into the accumulator to achieve a predetermined Target Weight Range (TWR).

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating safety trajectories. One of the methods comprises causing, by a robotic control system, execution of a robotic control plan by a plurality of robotic components in a robotic execution environment; generating a safety trajectory at each of a plurality of time points during the execution of the robotic control plan, including: obtaining data identifying a current position of a particular robotic component of the plurality of robotic components; generating, using the obtained data, a safety trajectory for the particular robotic component; and providing the safety trajectory to an emergency control system; determining that an emergency condition has been met; and in response, transferring control of the particular robotic component from the robotic control system to the emergency control system, comprising causing, by the emergency control system, execution of the safety trajectory by the particular robotic component.

A robot system includes a robot controller and an object robot including a first storage part storing a hardware identifier, individual discrimination data, and device specific data including an individual difference parameter. The same hardware identifier is assigned to the object robot having the same mechanism. The robot controller includes a second storage part storing common configuration information corresponding to the hardware identifier and the individual discrimination data and the individual difference parameter of the object robot, and a control part configured, in a case that the hardware identifier corresponding to the common configuration information stored in the second storage part and the hardware identifier assigned to the object robot are collated and matched with each other, to create hardware definition information of the object robot based on the common configuration information stored in the second storage part and the individual difference parameter read from the first storage part.

Apparatuses, systems, and techniques provide a policy that can be executed to cause a machine to move. In at least one embodiment, a first policy layer is provided to cause the machine to execute a first motion that causes the machine to accelerate to reach an unbiased state. A second policy layer is provided to cause the machine to execute a second motion without influencing the unbiased state to be reached by machine. The policy can comprise the first and second policy layers.

A control device for robot arm is provided that comprises: an elastic member comprising a palm portion and a finger portion, the palm portion being coupled to the finger portion, the elastic member being adapted to receive a part of body of a user; a detecting electrode located on an inner surface of the palm portion and configured to detect a surface electromyogram signal of the part of body for identifying a gesture of the part of body of the user; a sensor located on the elastic member for acquiring data relating to a three-dimensional motion of the part of body of the user to identify the three-dimensional motion of the part of body of the user, wherein the surface electromyogram signal and the data relating the three-dimensional motion are adaptable to be used to control the robot arm to perform the gesture and the three-dimensional motion.

A role switching method of robots with similar appearance includes: at a robot, the robot being capable of communicating with other robots within a predetermined range: identifying other robots having the same appearance as the robot itself within the predetermined range; and performing role exchange with the other robots having the same appearance as the robot itself within the predetermined range.

An inspection robot, and methods and a controller thereof are disclosed. An inspection robot may include an inspection chassis including a plurality of inspection sensors and coupled to at least one drive module to drive the robot over an inspection surface. The inspection robot may also include a controller including an inspection data circuit to interpret inspection base data, an inspection processing circuit to determine refined inspection data, and an inspection configuration circuit to determine an inspection response value in response to the refined inspection data. The controller may further include an inspection response circuit to, in response to the inspection response value, provide an inspection command value while the inspection robot is interrogating the inspection surface.

A collaborative-robot control system is provided in the invention. The collaborative-robot control system includes a plurality of test machines, a plurality of collaborative robots, a first control system and a second control system. The plurality of test machines are configured in a plurality of paths. When the second control system assigns a first collaborative robot of the plurality of collaborative robots in a waiting area to a first test machine in a first path of the plurality of paths and the first collaborative robot is being blocked by a second collaborative robot of the plurality of collaborative robots in the first path, the second control system generates a push-forward command and transmits the push-forward command to the first control system. The first control system sends the push-forward command to the second collaborative robot to order the second collaborative robot to leave the first path first.

A method and robot controller configured to obtain an inertia-vibration model of the robot arm. The inertia-vibration model defines a relationship between the inertia of the robot arm and the vibrational properties of said robot arm and have been by setting the robot arm in a plurality of different physical configurations and for each of said physical configurations of said robot arm obtaining the vibrational properties and the inertia the robot arm. The inertia-vibration model makes it possible to in a simple and efficient way to obtain the vibrational properties of different physical configurations of the robot arm whereby the robot arm can be controlled according to the vibrational properties of the robot arm. This makes it possible to reduce the vibrations of the robot arm during movement of the robot arm.

Provided are a multi-degree-of-freedom myoelectric artificial hand control system and a method for using same. The system comprises a robotic hand, a robotic wrist (2), a stump receiving cavity (1) and a data processor (3), wherein the robotic hand and the stump receiving cavity (1) are respectively mounted on two ends of the robotic wrist (2); a multi-channel myoelectric array electrode oversleeve, a control unit circuit board, and a battery are connected in the stump receiving cavity (1); and the other end of the control unit circuit board is connected to the robotic hand and the robotic wrist (2). The method for using the system comprises the following steps: (S1) a user wearing a multi-channel myoelectric array electrode oversleeve, and connecting a battery and a control unit circuit board; (S2) the user completing a gesture, collecting a surface electromyography signal and then uploading same to a data processor (3); (S3) the data processor (3) receiving the surface electromyography signal and inputting same into a neural network algorithm to generate a gesture prediction model; and (S4) the user controlling the multi-degree-of-freedom movement of the robotic wrist (2) and the robotic hand. By means of the system, continuous gestures and the gesture strength thereof can be identified, and multi-degree-of-freedom gestures can be made.