A method for controlling the motion of a mobile warning triangle for suitable placement on a roadway acquires information as to color of the lane markings detected by a sensor. When the mobile warning triangle is first placed on the roadway, the sensor is preset in position to detect the lane marking. White or yellow color information of the lane marking or of the black-colored roadway are detected or are not detected by the sensor, and deviations from a required path are recognized when different colors are received in certain combinations by the sensor. If no deviation is recognized in the colors, the mobile warning triangle continues moving forward. If a deviation in colors is recognized, the mobile warning triangle is controlled to hunt to the left and right through one or more predetermined angles to try to detect or redetect the lane marking.

A system is described for determining the position of a vehicle on a site and for calculating a trajectory, including at least one vehicle, at least one auxiliary device and at least one reflector element, the at least one reflector element being mounted in the surroundings of the vehicle along a designated route section and the auxiliary device being suitable for transmitting and receiving electromagnetic beams. A method is also described.

Systems, devices, and methods for docking a mobile robot to a dock using distinct visual fiducial markers on the dock are disclosed. A mobile robot system is provided that includes a dock and a mobile cleaning robot. The dock includes a first fiducial marker in a first plane on the dock and second one or more fiducial markers in a second plane different from the first plane. The mobile cleaning robot includes a visual system to detect the first and the second one or more fiducial markers, and a controller circuit to recognize the dock, and to determine a pose or heading direction of the mobile cleaning robot based on the detected first and the second one or more fiducial markers. The mobile drive system can adjust its heading direction, and drive to the dock according to the adjusted heading direction.

A system for an autonomous vehicle by providing lane markers on the road for which a vehicle will read and navigate the road. The vehicle transmits a discovery signal and is returned from the marker to indicate the position on the road and how to proceed on the road. The system uses either an autonomous control system or 3D map navigation database to determine the direction of the vehicle in real time.

Examples relate to simultaneous localization and calibration. An example implementation may involve receiving sensor data indicative of markers detected by a sensor on a vehicle located at vehicle poses within an environment, and determining a pose graph representing the vehicle poses and the markers. For instance, the pose graph may include edges associated with a cost function representing a distance measurement between matching marker detections at different vehicle poses. The distance measurement may incorporate the different vehicle poses and a sensor pose on the vehicle. The implementation may further involve determining a sensor pose transform representing the sensor pose on the vehicle that optimizes the cost function associated with the edges in the pose graph, and providing the sensor pose transform. In further examples, motion model parameters of the vehicle may be optimized as part of a graph-based system as well or instead of sensor calibration.

One method disclosed includes identifying, in a map of markers fixed in an environment, two co-located markers within a threshold distance of each other, where each of the two co-located markers has a non-overlapping visibility region. The method further includes determining a set of detected markers based on sensor data from a robotic device. The method additionally includes identifying, from the set of detected markers, a detected marker proximate to a first marker of the two co-located markers. The method also includes enforcing a visibility constraint based on the non-overlapping visibility region of each of the two co-located markers to determine an association between the detected marker and a second marker of the two co-located markers. The method further includes determining a location of the robotic device in the environment relative to the map based on the determined association.

In certain embodiments, a method includes accessing image information for a scene in a movement path of a mobile robot. The image includes image information for each of a plurality of pixels of the scene, the image information comprising respective intensity values and respective distance values. The method includes analyzing the image information to determine whether to modify the movement path of the mobile robot. The method includes initiating, in response to determining according to the image information to modify the movement path of the mobile robot, sending of a command to a drive subsystem of the mobile robot to modify the movement path of the mobile robot.

One variation of a method for autonomously navigating along a crosswalk includes: at a first time, navigating autonomously along a sidewalk toward a crosswalk coinciding with a navigation route assigned to the autonomous vehicle; recording optical data of a scene proximal the autonomous vehicle via an optical sensor integrated into the autonomous vehicle; aligning an anteroposterior axis of the autonomous vehicle to the crosswalk detected in the optical data; identifying a pedestrian proximal the crosswalk in the optical data; in response to the pedestrian entering the crosswalk at a second time succeeding the first time, predicting right of way of the autonomous vehicle to enter the crosswalk; and, in response to predicting right of the autonomous vehicle to enter the crosswalk, autonomously navigating from the sidewalk into the crosswalk and autonomously navigating along the crosswalk to an opposing sidewalk according to the navigation route.

An autonomous metal-plate inspection apparatus, an inspection method, and a method for manufacturing a metal plate by using the inspection apparatus. The autonomous metal-plate inspection apparatus includes a carriage that travels on a surface of a metal plate, a navigational transmitter or a navigational receiver, an inspection device that includes flaw detection head including an inspection sensor, which scans an inspection region of the metal plate, and an inspection-result generation unit for generating an inspection result, and a control unit that performs, on the basis of a position of the carriage measured by the position measurement system and a target position, control the carriage to autonomously travel to the target position and control the flaw detection head to scan. The inspection-result generation unit generates the inspection result on the basis of inspection information obtained by the inspection sensor and position information of the flaw detection head.

Markers and a system for use for autonomous vehicles which can help autonomous vehicles to be aware of their surroundings and/or their spatial location. Such markers can include metallic signage having one or more openings and which can include a front that is spaced a distance from a backing plate. The markers can also include patterns that are stamped, cut or otherwise formed in or on a roadway. When a vehicle traverses over the patterns, a sensor, which can include a sound sensor, can detect the sound or vibration produced by the pattern. Once the pattern is detected, the autonomous vehicle can access a database or other repository of patterns (including but not limited to internal memory) and thus obtain information about the location that the vehicle is traversing.