A manufacturing system includes a vehicle configured to facilitate movement of a product throughout a manufacturing environment. The vehicle assembly includes a chassis, an interface coupled to the chassis and configured to support the product, and a sensor coupled to the interface. The sensor is operatively coupled to a controller, which is configured to receive sensor data, receive current stage of assembly of a product, determine an expected force based on the current stage of assembly, and compare the measured force and expected force. In response to a determination that the measured force differs from the expected force, the controller provides a notification to the user of the current status of the product.

The operations of a computer-implemented method include obtaining a topological map of an environment including a series of waypoints and a series of edges. Each edge topologically connects a corresponding pair of adjacent waypoints. The edges represent traversable routes for a robot. The operations include determining, using the topological map and sensor data captured by the robot, one or more candidate alternate edges. Each candidate alternate edge potentially connects a corresponding pair of waypoints that are not connected by one of the edges. For each respective candidate alternate edge, the operations include determining, using the sensor data, whether the robot can traverse the respective candidate alternate edge without colliding with an obstacle and, when the robot can traverse the respective candidate alternate edge, confirming the respective candidate alternate edge as a respective alternate edge. The operations include updating, using nonlinear optimization and the confirmed alternate edges, the topological map.

In conventional robot navigation techniques learning and planning algorithms act independently without guiding each other simultaneously. A method and system for robotic navigation with simultaneous local path planning and learning is disclosed. The method discloses an approach to learn and plan simultaneously by assisting each other and improve the overall system performance. The planner acts as an actuator and helps to balance exploration and exploitation in the learning algorithm. The synergy between dynamic window approach (DWA) as a planning algorithm and a disclosed Next best Q-learning (NBQ) as a learning algorithm offers an efficient local planning algorithm. Unlike the traditional Q-learning, dimension of Q-tree in the NBQ is dynamic and does not require to define a priori.

A computer implemented method includes obtaining historical operation data relative to a plurality of historical operations, the historical operation data including historical machine data, historical worksite data, historical productivity data, and historical logistics data; obtaining current operation data relative to an underway or upcoming operation, the current operation data including current machine data and current worksite data; generating, based on the obtained historical operation data and the obtained current operation data, an operation plan output relative to the underway or upcoming operation, the operation plan output including one or more of: (i) one or more machine routes; (ii) one or more sub-operation locations; (iii) one or more operation plan maps; or a combination of (i), (ii), and (iii); and generating control signals to control one or more mobile agricultural work machines based on the operation plan output.

An autonomous mobile robot (AMR) wheelchair capable of achieving autonomous monitoring, operation, and guidance includes a wheelchair frame, fixed moving wheels mounted on front and rear sides of a bottom of the wheelchair frame to achieve movement of the wheelchair, a foot rest mounted at a front part of the wheelchair frame to support the feet of a user, and arm rests arranged on two sides of the wheelchair frame. The front moving wheels further has a function of adjusting a travelling direction of the wheelchair. Connecting frames are arranged at the bottom of the wheelchair frame; the connecting frames are movably provided with clamping frames; and an AMR device is clamped and released by adjusting a distance between the two clamping frames, without another auxiliary tool, thereby achieving an effect of conveniently removing the AMR device and facilitating updating and maintenance of the AMR device.

A method and apparatus of generating a path for autonomous navigation of a mobile computing apparatus is provided. The mobile computing apparatus includes one or more processors configured to map a set global path, which connects a current position of the mobile computing apparatus with a future destination of the mobile computing apparatus based on a topology map, to a real-time generated occupancy grid map that represents, based on sensor data of a surrounding environment of the mobile computing apparatus, an un-drivable area and a drivable area in the surrounding environment, and generate a local path, for a traveling of the mobile computing apparatus, connecting the current position with a sub-waypoint that corresponds to the drivable area in response to a next waypoint, to which the mobile computing apparatus is set to travel based on the global path, being determined to correspond to the un-drivable area.

The present disclosure provides an automatic pool cleaning apparatus, a control method and a computer storage medium. The control method includes: obtaining predetermined information required for the automatic pool cleaning apparatus to perform repositioning; and determining whether the predetermined information satisfies a predetermined condition for the automatic pool cleaning apparatus to perform the repositioning, in a case where the predetermined condition is satisfied, controlling the automatic pool cleaning apparatus to perform the repositioning.