A flux sensing system includes a memory and a processor in communication with the memory and at least one sensing device, the memory storing a plurality of capabilities and a plurality of semantic fluxes associated with the plurality of capabilities. Based on inputs from the at least one sensing device, the computing system is configured to determine an active servicing capability associated with a first semantic flux and/or a consumer interest associated with a second semantic flux and match the interest with the capability based on semantic drift inference.

Methods are described that perform a dispatched consumer-to-store return or swap logistics operation for an item being replaced using a modular autonomous bot apparatus assembly and a dispatch server. The method begins with receiving a return operation dispatch command that includes identifier information, transport parameters, and designated pickup information for the item being replaced/returned, along with authentication information related to an authorized supplier of the item being replaced. Modular components of the bot apparatus are verified to be compatible with the dispatched logistics operation. The MAM then autonomously causes the bot apparatus to move to the designated pickup location, notifies the authorized supplier of an approaching pickup, receives supplier authorization input to permissively allow access to a payload area within the bot apparatus, monitors loading as the item being replaced is received along with return documentation, and then autonomously causes movement of the bot apparatus back to the origin location.

The present technique relates to an information processing apparatus, an information processing method, and a program capable of easily setting a highly-reliable entry prohibited area. An information processing apparatus according to one aspect of the present technique sets a parameter of each area used for an action plan for a mobile object on the basis of a person's recognition state during movement estimated by people flow data. The present technique may be applied to an information processing apparatus that controls an autonomous mobile robot.

A control system for controlling a plurality of robots using artificial intelligence includes a communication unit configured to receive user information of each of a plurality of unit zones in which the plurality of robots is disposed, and a processor configured to calculate a plurality of densities respectively corresponding to the plurality of unit zones based on the user information of each unit zone, calculate average densities of a plurality of group zones using the plurality of calculated densities, determine respective priorities of the plurality of group zones based on the calculated average densities, and control movement of one or more of the plurality of robots based on the determined priorities.

A robot control system according to the present embodiment includes a plurality of mobile robots that moves autonomously in a facility and a control device that controls the mobile robots. When the control device detects that two or more of the mobile robots are in a recovery requiring state, the control device notifies that the two or more mobile robots are in the recovery requiring state, together with priorities of the two or more mobile robots.

A robotic door lock includes a lockable spinner having a spinner shell coupled to a bolt rail and an axial profile coupled to a door handle or knob. A processor selectively engages the spinner shell with the axial profile via an actuator to enable the manipulation of the bolt. The robotic lock has a wireless module, an actuator, and a processor in communication with the actuator and a wireless module. The wireless module uses a wireless energy harvester configured to receive energy from a user device or a post infrastructure to power the processor, the actuator and the memory. The wireless energy harvester may be connected to an internal energy storage.

A robot moves about an environment and may interact with a user. A waypoint specifies where the robot is to move to with respect to the user while a proxemic cost map is used to plan the path to the waypoint. User input or preferences may be used to modify the waypoint or the proxemic cost map. The waypoint may specify a particular distance and bearing with respect to the user. The proxemic cost map may be oriented with respect to the user and specifies costs for particular areas. For example, an area immediately behind the user may have a very high cost while an area in front of the user may have a low cost. Based on the waypoint and the proxemic cost map, a path is selected and the robot moves along that path, avoiding the high cost areas in favor of the low cost areas if possible.

A flux system includes a memory and a processor in communication with the memory and a sensing device, the memory storing a plurality of capabilities and a plurality of semantic fluxes associated with the plurality of capabilities. The computing system is configured to infer a semantic based on received inputs and to infer an activity interest semantic based on an input, and to assign at least one augmentation servicing agent to service an activity interest based on semantic matching.

An exemplary embodiment of the present disclosure provides a method, an apparatus, a system, an electronic device and a storage medium for robot navigation. The robot navigation system includes: a first infrared receiving unit, a second infrared receiving unit, a distance measuring unit, and a processing unit, where the first infrared receiving unit and the second infrared receiving unit are disposed on a robot to receive a first infrared signal and a second infrared signal from an infrared transmission unit respectively; the distance measuring unit is disposed on the robot to obtain a distance signal indicating a distance between the robot and the target device; the processing unit is configured to: obtain the first infrared signal, the second infrared signal and the distance signal, control a moving direction of the robot based on the first infrared signal and the second infrared signal, and control the robot to move to the target device in response to determining that the robot enters a docking scope based on the distance signal. In the embodiments of the present disclosure, the costs of the navigation system are reduced with the accuracy improved.

A method for identifying a moving object in a three-dimensional space and a robot for implementing same is provided. The robot includes a sensing module for calculating height and position information of an object by using two or more sensing units; a movement unit for moving the robot; a map storage unit for storing a three-dimensional map including the height and position information of the object, calculated by the sensing module, in a space in which the robot is moving; and a control unit for controlling the sensing module, the movement unit, and the map storage unit, converting the height and position information of the object calculated by the sensing module into global coordinates, storing, in the three-dimensional map, the height and position information of the object converted into the global coordinates, and removing, from the three-dimensional map, a moving object among objects stored in the map storage unit.