A electronic device comprising a sensor unit, a memory, and at least one processor that: obtains, by the sensor unit, first sensing data including an image captured at the location; obtains map information on the basis of the first sensing data; combines the first sensing data and the second sensing data to obtain first mapping information and stores same in the memory; obtains second mapping information by removing data corresponding to a pre-configured condition corresponding from the stored first mapping information; identifies spatial information including feature data corresponding to a space included in the map information on the basis of the second mapping information; and controls traveling of the electronic device on the basis of the map information and the spatial information.

An autonomous mobile robot and an operating method thereof are provided. The autonomous mobile robot includes a movement module, a detection module, a control module and an interaction module. The control module includes a determination unit and a navigation unit. The determination unit determines whether there is an obstacle near or on a predetermined path of the autonomous mobile robot according to the environment information. When the obstacle is on the predetermined path, the navigation unit decides an obstacle avoidance strategy according to the environment information and the type of the obstacle. The obstacle avoidance strategy at least includes moving along a side path, stopping aside to yield, moving backward and stopping at a yielding point to yield, and detouring. When the obstacle is near or on the predetermined path, the interaction module performs an interaction action according to the obstacle avoidance strategy and the type of the obstacle.

There is provided a computer implemented method of controlling movement of an object, comprising: accessing a current image of a surface relative to an object at a current location, wherein an imaging sensor is set to capture the current image depicting an overlap with a previously captured image of the surface when the object was at a previous location, registering the current image to the overlap of the previously captured image, computing the current location of the object relative to a reference location according to an analysis of the registration, and feeding the current location into a controller for controlling movement of the object.

Methods and devices for actively modifying a field of view of an autonomous vehicle in view of constraints are disclosed. In one embodiment, an example method is disclosed that includes causing a sensor in an autonomous vehicle to sense information about an environment in a first field of view, where a portion of the environment is obscured in the first field of view. The example method further includes determining a desired field of view in which the portion of the environment is not obscured and, based on the desired field of view and a set of constraints for the vehicle, determining a second field of view in which the portion of the environment is less obscured than in the first field of view. The example method further includes modifying a position of the vehicle, thereby causing the sensor to sense information in the second field of view.

According to the embodiments described herein, system and methods for determining relative pose of materials handling vehicles in an industrial environment may include utilizing ultra-wideband (UWB) antenna array systems respectively mounted on the materials handling vehicles to send mutually received information to determine the relative pose between the vehicles, determining one or more fields of each materials handling vehicle, and determining one or more overlapping fields between the materials handling vehicles based on the determined one or more fields and the relative pose. A vehicle control may be implemented based on the determined relative pose and the overlapping fields as a field enforcement, such as a control action to avoid collision between the vehicles.

A system for 3D surveying of an environment by an unmanned ground vehicle (UGV) and an unmanned aerial vehicle (UAV) has two lidar devices. A reference unit has a first and a second marker in a spatially fixed arrangement. An automatic detection of the first marker is carried out for a coordinative measurement by the first lidar device to determine relative position data for providing relative position information of the first marker with respect to the first lidar device. The relative position data and spatial 3D information is used for an automatic detection and a coordinative measurement of the second marker by the second lidar device. The coordinative measurements are used for a referencing of lidar data of the UGV lidar device and lidar data of the UAV lidar device with respect to a common coordinate system.

A control device includes a storage device which has stored a program, and a hardware processor, in which the hardware processor executes the program stored in the storage device, thereby acquiring a peripheral image of the mobile object, which is an image captured by a fisheye camera mounted on a mobile object, calculating an instruction regarding future traveling of the mobile object as a base trajectory in an orthogonal coordinate system, coordinate-converting the acquired base trajectory in the orthogonal coordinate system into a base trajectory in a fisheye camera coordinate system, calculating a risk of the base trajectory in the fisheye camera coordinate system on the basis of the peripheral image, and the base trajectory in the fisheye camera coordinate system, and calculating a traveling trajectory by modifying the base trajectory in the orthogonal coordinate system on the basis of the risk of the base trajectory in the fisheye camera coordinate system.

Lighting control systems may be commissioned for programming and/or control with the aid of a mobile device. Design software may be used to create a floor plan of how the lighting control system may be designed. The design software may generate floor plan identifiers for each lighting fixture, or group of lighting fixtures. During commissioning of the lighting control system, the mobile device may be used to help identify the lighting devices that have been installed in the physical space. The mobile device may receive a communication from each lighting control device that indicates a unique identifier of the lighting control device. The unique identifier may be communicated by visible light communication (VLC) or RF communication. The unique identifier may be associated with the floor plan identifier for communication of digital messages to lighting fixtures installed in the locations indicated in the floor plan identifier.

This disclosure relates generally to systems and methods for object detection using a geometric semantic map based robot navigation using an architecture to empower a robot to navigate an indoor environment with logical decision making at each intermediate stage. The decision making is further enhanced by knowledge on actuation capability of the robots and that of scenes, objects and their relations maintained in an ontological form. The robot navigates based on a Geometric Semantic map which is a relational combination of geometric and semantic map. In comparison to traditional approaches, the robot's primary task here is not to map the environment, but to reach a target object. Thus, a goal given to the robot is to find an object in an unknown environment with no navigational map and only egocentric RGB camera perception.

According to the embodiments described herein, system and methods for determining relative pose of materials handling vehicles in an industrial environment may include utilizing ultra-wideband (UWB) antenna array systems respective mounted on the materials handling vehicles to send mutually received information to determine the relative pose between the vehicles, determining one or more fields of each materials handling vehicle, and determining one or more overlapping fields between the materials handling vehicles based on the determined one or more fields and the relative pose. A vehicle control may be implemented based on the determined relative pose and the overlapping fields as a field enforcement, such as a control action to avoid collision between the vehicles.