Unmanned ground vehicle (UGV) includes a rotary joint having an axis of rotation. A rotary joint actuator is responsive to at least one control signal and is configured to cause a rotatable portion of the rotary joint to rotate relative to the vehicle chassis about the rotary joint axis of rotation. A stabilizer flipper having an elongated length is attached to the rotatable portion. Consequently, rotation of the rotatable portion about the rotary joint axis of rotation results in a change of orientation of the stabilizer flipper relative to the chassis. This change in orientation can range between a lateral direction and an longitudinal direction with respect to the vehicle chassis.

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 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 system includes an inspection robot comprising a plurality of sensor sleds; a plurality of ultra-sonic (UT) sensors; a couplant chamber mounted to each of the plurality of sleds, each couplant chamber comprising: a cone, the cone comprising a cone tip portion at an inspection surface end of the cone; a sensor mounting end opposite the cone tip portion; a couplant entry fluidly coupled to the cone at a position between the cone tip portion and the sensor mounting end; and wherein each of the UT sensors is mounted to the sensor mounting end of one of the couplant chambers.

A flexible inspection system includes a robot with a plurality of scanners and a robot controller. The robot controller is configured to receive a vehicle inspection protocol (VIP) for a vehicle being assembled on an assembly line. The VIP includes checkpoints to be scanned on the vehicle and the checkpoints correspond to components installed on the vehicle and connections between components installed on the vehicle. The robot controller commands the robot to move the plurality of scanners per the VIP such that the checkpoints are scanned. A characteristic of each checkpoint is recorded and compared to a reference characteristic such that a pass or no-pass determination of each checkpoint is provided. A vehicle inspection report with the pass/no-pass determinations is provided to an operator such that operator inspections and/or repairs of the checkpoints are made.

A repair welding control device includes a processor. The processor is configured to acquire repair portion information indicating a welded portion where repair welding is performed among welded portions in a workpiece welded by a first welding program, and generate a second welding program by correcting the first welding program based on the repair portion information.

A survey system includes a controller storing a map comprising a plurality of nodes representing data capture points of the environment. The controller is configured to segment the plurality of nodes into a plurality of communities, where each community from among the plurality of communities includes a set of nodes from among the plurality of nodes. The controller is configured to generate, for each community from among the plurality of communities, one or more traversability scores. The controller is configured to assign, for each community from among the plurality of communities, at least one robot from among a plurality of robots to survey the community based on the one or more traversability scores. The controller is configured to deploy, for each community from among the plurality of communities, at least one of the plurality of robots based on the plurality of robots assigned to the community.

Methods of performing a plurality of operations within a region of a part utilizing an end effector of a robot and robots that perform the methods are disclosed herein. The methods include collecting a spatial representation of the part and aligning a predetermined raster scan pattern for movement of the end effector relative to the part with the spatial representation of the part. The methods also include defining a plurality of normality vectors for the part at a plurality of predetermined operation locations for operation of the end effector. The methods further include moving the end effector relative to the part and along the predetermined raster scan pattern. The methods also include orienting the end effector such that an operation device of the end effector faces toward each operation location along a corresponding normality vector and executing a corresponding operation of the plurality of operations with the operation device.

A system includes an inspection robot having a plurality of input sensors, the plurality of input sensors distributed horizontally relative to an inspection surface and configured to provide inspection data of the inspection surface at selected horizontal positions; a controller, comprising: a position definition circuit structured to determine an inspection robot position of the inspection robot on the inspection surface; a data positioning circuit structured to interpret the inspection data, and to correlate the inspection data to the inspection robot position on the inspection surface; and wherein the data positioning circuit is further structured to determine position informed inspection data in response to the correlating of the inspection data with the inspection robot position.

A system including an inspection robot having a plurality of sensors, a further sensor, and a controller. The controller having circuitry to receive inspection data with a first resolution from the plurality of sensors, determine a characteristic on the inspection surface based on the inspection data, and provide an inspection operation adjustment in response to the characteristic, wherein the inspection operation adjustment includes a change from the first resolution to a second resolution. The change from the first resolution to the second resolution includes enabling the further sensor where the further sensor is at least one of: horizontally distributed with or vertically displaced from the plurality of sensors relative to a travel path of the plurality of sensors, and at least one of: offset in alignment from the travel path of the plurality of sensors, or operated out of phase with the plurality of sensors.