A method for multipoint purification by a robotic air purifier, comprising the following steps: S1: establishing a coordinate map of an area to be purified; S2: the robotic air purifier moves within the area to be purified according to a preconfigured movement model, measuring air quality, remembering as level-1 pollution sources those points where a pollution value exceeds a preset threshold, and marking the coordinates of said points on the coordinate map; S3: when having completed its movement over the area to be purified, the robotic air purifier moves to each level-1 pollution source point and performs an initial purification process, while at the same time measuring air quality, continuing in this way until the air quality at all said level-1 pollution sources complies with requirements.

A sleeve worn on an arm allows detection of gestures by an array of sensors. Electromyography, inertial, and magnetic field sensors provide data that is processed to categorize gestures and translate the gestures into commands for robotic systems. Machine learning allows training of gestures to increase accuracy of detection for different users.

Described is related to a dual function robotic cleaning device for removing harmful chemical pollutants, viruses, unpleasant odors as well as particulates from indoor air in addition to cleaning dust and debris from the ground or floors. The device has a floor cleaning unit and an indoor air purification unit integrated in the same body which can operate automatically according to indoor air pollution levels as well as by a user's instructions. The air purification unit consists of a virus zapping filter for eliminating airborne viruses, a chemical and odor filter for removing toxic chemical pollutants and unpleasant odors, a particulate filter for trapping PM2.5, and a chemical sensor for detecting chemical pollutant levels in indoor air, which feeds pollution values to the control unit of the device to trigger the air cleaning operation.

A mechanical equipment control system includes a mechanical apparatus, a load ratio detection circuit, and an integration control circuit. The mechanical apparatus includes a motor which is configured to drive the mechanical apparatus. The load ratio detection circuit is configured to detect a load ratio of the motor. The integration control circuit is configured to control the mechanical apparatus based on an operation parameter while keeping the load ratio in an allowable load state.

A tool control system may include: a tactile sensor configured to, when a tool holds a target object and slides the target object downward across the tool, obtain tactile sensing data from the tool; one or more memories configured to store a target velocity and computer-readable instructions; and one or more processors configured execute the computer-readable instructions to: receive the tactile sensing data from the tactile sensor; estimate a velocity of the target object based on the tactile sensing data, by using one or more neural networks that are trained based on a training image of an sample object captured while the sample object is sliding down; and generate a control parameter of the tool based on the estimated velocity and the target velocity.

Systems and methods are described, and an example system includes a transport bin configured to carry a baggage item and having spatial reference frame marking detectable by electromagnetic scan and by machine vision. The system includes a robotic arm apparatus at an inspection area, and includes a switched path baggage conveyor that, responsive to electromagnetic scan detection of an object-of-interest (OOI) within the baggage item, conveys the transport bin to the inspection area. The electromagnetic scan generates OOI geometric position information indicating geometric position of the OOI relative to the spatial reference frame marking. The robotic arm apparatus, responsive to receiving the transport bin, uses machine vision to detect orientation of the spatial reference frame marking, then translates OOI geometric position information to local reference frame, for robotic opening of the baggage item, and robotic accessing and contact swab testing on the OOI.

A method of operating a robot including a vacuum port for engaging an item, e.g. a wafer, is disclosed. The method includes operating, by a computer system, the robot in a first state, detecting using a vacuum sensor, a transition of a vacuum parameter from a first vacuum parameter zone to a second parameter zone in a plurality of vacuum parameter zones. Based on detecting the transition of the vacuum parameter from the first vacuum parameter zone to the second vacuum parameter zone, the operating state of the robot is altered from the first state to a second state. Also disclosed is an item transfer robot as part of an item transfer system.

A robotic assembly associated with gripping an object may determine, using an angle sensor, a relative position of a first gripping arm in relation to a second gripping arm of a robotic assembly. The robotic assembly may separate, using an actuator, the first gripping arm and the second gripping arm of the robotic assembly. The robotic assembly may position the gripping arms around an object, so the first gripping arm and second gripping arm accommodate the object. The robotic assembly may then join the first gripping arm and the second gripping arm until the first roller, second roller, and third roller are in contact with the object. The robotic assembly may apply pressure to the object using a plurality of compression springs between the first gripping arm and second gripping arm allowing the robotic assembly to grip the object.

An actuator system that picks up workpieces aims to shorten tact time and to reduce damages to workpieces. The actuator system includes an actuator that picks up a workpiece, an external force detection sensor that detects a physical quantity that is correlated with an external force that is applied to the workpiece, a head unit that is connected to the actuator and the external force detection sensor without a communication network, the head unit being configured to control the actuator based on a sensing result from the external force detection sensor when a pickup request signal that is a signal requesting pickup of the workpiece is received, and a control device that is connected to the head unit over the communication network, the control device being configured to transmit the pickup request signal to the head unit.

A gas pressure detection device 10 detects a decrease in a pressure of gas of a gas balancer 8 of a robot 2. The gas pressure detection device 10 includes a calculating part configured to calculate a parameter Rt(θ) indicating a magnitude relation between a reference pressure Pa(θ) at a rotational angle θ of a rotary arm 14 and a measured pressure Pt(θ) measured at the rotational angle θ, calculate a plurality of parameters Rt(θ) based on a plurality of measured pressures Pt(θ) at different measurement times, and calculate a moving average Rtj(θ) of the parameter Rt(θ) at a measurement time tj that is a j-th measurement time of the measured pressure Pt(θ) (j representing a natural number of 2 or above), and a determining part configured to compare the moving average Rtj(θ) with a reference value R to detect the decrease in the pressure of the gas.