Abstract: A brick-and-mortar (BAM) store control system uses sensors and wireless transceivers to track customers, merchant representatives, devices, and/or objects within a BAM store area. The system can identify and track product and/or service inventory within the BAM store area and/or in individual's personal inventories, for instance by detecting movements of objects by individuals in sensor data. The system can generate inventory replenishment schedules, for instance based on inventory quantity patterns. The system can provide recommendations to customers and/or merchants, for example recommending products that customers have interacted with. The system can identify individuals and/or objects using a machine learning algorithm, which can learn based on feedback. The system can generate temporary identifiers for unrecognized individuals or objects, which it can merge or convert into long-term identifiers as more information is received.

Abstract: Disclosed are autonomous vehicles that may autonomously navigate at least a portion of a route defined by a service request allocator. The autonomous vehicle may, at a certain portion of the route, request remote assistance. In response to the request, an operator may provide input to a console that indicates control positions for one or more vehicle controls such as steering position, brake position, and/or accelerator position. A command is sent to the autonomous vehicle indicating how the vehicle should proceed along the route. When the vehicle reaches a location where remote assistance is no longer required, the autonomous vehicle is released from manual control and may then continue executing the route under autonomous control.

Abstract: A brick-and-mortar (BAM) store control system uses sensors and wireless transceivers to track customers, merchant representatives, devices, and/or objects within a BAM store area. The system can identify and track product and/or service inventory within the BAM store area and/or in individual's personal inventories, for instance by detecting movements of objects by individuals in sensor data. The system can generate inventory replenishment schedules, for instance based on inventory quantity patterns. The system can provide recommendations to customers and/or merchants, for example recommending products that customers have interacted with. The system can identify individuals and/or objects using a machine learning algorithm, which can learn based on feedback. The system can generate temporary identifiers for unrecognized individuals or objects, which it can merge or convert into long-term identifiers as more information is received.

Abstract: Disclosed are autonomous vehicles that may autonomously navigate at least a portion of a route defined by a service request allocator. The autonomous vehicle may, at a certain portion of the route, request remote assistance. In response to the request, an operator may provide input to a console that indicates control positions for one or more vehicle controls such as steering position, brake position, and/or accelerator position. A command is sent to the autonomous vehicle indicating how the vehicle should proceed along the route. When the vehicle reaches a location where remote assistance is no longer required, the autonomous vehicle is released from manual control and may then continue executing the route under autonomous control.