The present disclosure relates to a system and a method of controlling the movement of a tracked mobile mining machine having one or more articulated vehicle units. The control system works by taking input from manual or automated input means, the input serving as a set operating value for at least one driving parameter. The controller generates control signals, which are sent to regulating means that actuate the motor of the mobile mining machine. Using sensors on the machine, actual values of the driving parameter are measured in real-time and fed to the controller for comparison with the original set values. Any difference in the values is compensated for when the controller sends control signals to the regulating means causing readjustment of the driving parameter of the mining machine. The control system is applicable to crawler-driven powered vehicle units to ensure synchronous crawler movement for both linear and non-linear paths.

Systems, methods, and autonomous vehicles for detecting road marking points from LiDAR data may obtain a LiDAR dataset generated by a LiDAR system; process, for each laser emitter of the LiDAR system, a point cloud associated with that laser emitter by: determining, for each point in the point cloud, based on a gradient of intensity at that point, whether that point corresponds to a gradient edge point; and determining, based on intensities of points in an interior segment of points between at least one candidate pair of gradient edge points and intensities of points in exterior segments of points outside the at least one candidate pair of gradient edge points, whether that candidate pair of gradient edge points corresponds to a road marking edge; and aggregate, from the processing of the plurality of point clouds, candidate pairs of gradient edge points determined to correspond to road marking edges.

A collision avoidance apparatus for use with an automated guided vehicle (AGV) includes: an object detection sensor assembly; a controller in electronic communication with the sensor assembly; the object detection sensor assembly configured to generate a detection signal to define a sensing region and receive a reflected detection signal; the controller configured to: process the reflected signal to detect presence of an object based on a parameter of the reflected signal, define a boundary within the sensing region, dynamically adjust the size and/or shape of the boundary, and determine if the detected object is located within the boundary.

The disclosed embodiments include a method for automating alignment of image data captured of a three-dimensional (3D) physical structure with a computer model of the 3D physical structure. The method can include obtaining two-dimensional (2D) images of the 3D physical structure undergoing construction, detecting fiducial markers corresponding to control points in the 2D images, and determining a transformation function based on the control points. The method can further include obtaining more 2D images, detecting other fiducial markers, and aligning image data to a computer model by utilizing the transformation function. The method can further include refining an alignment by utilizing a refinement transformation based on 3D physical elements of the 3D physical structure.

An autonomous mobile robot (AMR) for transferring a component part in a process line of a production factory may include, a sensor unit configured to detect an obstacle in a travel path, an interface unit configured to identify coordinates of a waypoint and set an accuracy zone having a circular area around the waypoint, an omni-directional waypoint generation unit configured to obtain the travel path in a curved line which is aligned to tangentially meet a tangent vector of the circular area, a driving unit configured to generate a driving torque for driving the AMR, and a controller electrically connected to the sensor unit, the interface unit, the omni-directional waypoint generation unit and the driving unit and configured to control the driving unit to move the AMR along the travel path toward the waypoint, and when a current position of the AMR enters an effective range of the accuracy zone, to move the AMR toward the destination point without further moving toward the waypoint.

A method for generating an area map for a floor processing device, wherein first and second floor processing devices detect feature data of an environment and process them into first and second area maps. The first floor processing device identifies an object based on a unique identifier of the object as an anchor point and stores relative positional information of the anchor point in a coordinate system of the first area map. The second floor processing device recognizes the same object as an anchor point known to the second floor processing device, and stores relative positional information of the anchor point in a coordinate system of the second area map. The first and second area maps are combined into a common global area map based on the relative positional information of the anchor point contained therein, and the unique identifier is a code that clearly identifies the object.

In an example, a method comprises, for an autonomous vehicle: coarsely positioning a first signal beam emitter located on the vehicle in line with a first alignment target and coarsely positioning a second signal beam emitter located on the vehicle in line with a second alignment target, wherein the first and second alignment targets are each aligned with a predefined grid. The method may include emitting a first signal beam from the first signal beam emitter towards the first alignment target and emitting a second signal beam from the second signal beam emitter towards the second alignment target. The method may further include monitoring a first return signal beam from the first alignment target and adjusting at least one of a position and an orientation of the vehicle based at least in part on the first return signal beam and determining that alignment is complete based at least in part on the first return signal beam.

A mobile printing robot system for printing a construction layout. The method addresses a problem that occurs when there is a loss of a tracking lock to an absolute positioning device, such as a total station. In a construction site, a line of sight between a mobile robot and an absolute positioning device may be lost when the mobile robot moves into a shadowed region behind an obstacle, such as a column. The mobile printing robot may use its local sensor data to continue to print until a maximum estimated position is reached. The mobile robot may also provide position updates to the absolute positioning device to aid it to regain a track lock when the mobile robot emerged from the shadowed region.

A mobile robot includes a communication unit that communicates with another mobile robot, a sensing unit for sensing the other mobile robot existing in a detection area encompassing a predetermined projected angle with respect to the front of a main body of the mobile robot, and a control unit configured for rotating the main body so that the other mobile robot is sensed in the detection area. The communication unit transmits a control signal configured to cause the other mobile robot to travel in a linear direction by a predetermined distance, to the other mobile robot when the other mobile robot is present in the detection area.

Embodiments are provided that include receiving sensor data from a sensor positioned at a plurality of positions in an environment. The environment includes a plurality of landmarks. The embodiments also include determining, based on the sensor data, a subset of the plurality of landmarks detected at each of the plurality of positions. The embodiments further include determining, based on the subset of the plurality of landmarks detected at each of the plurality of positions, a detection frequency of each landmark. The embodiments additionally include determining, based on the determined detection frequency of each landmark, a localization viability metric associated with each landmark. The embodiments still further include providing for display, via a user interface, a map of the environment. The map includes an indication of the localization viability metric associated with each landmark.