An autonomous vehicle receives geographic location data defined via a mobile computing device operated by a user. The geographic location data is indicative of a device position of the mobile computing device. The autonomous vehicle also receives image data generated by the mobile computing device. The image data is indicative of a surrounding position nearby the device position. The surrounding position is selected from an image captured by a camera of the mobile computing device. A requested vehicle position (e.g., a pick-up or drop-off location) is set for a trip of the user in the autonomous vehicle based on the geographic location data and the image data. A route from a current vehicle position of the autonomous vehicle to the requested vehicle position for the trip of the user in the autonomous vehicle is generated. Moreover, the autonomous vehicle can follow the route to the requested vehicle position.

A vehicle may include a frame structure, a body mounted to the frame structure, and a vehicle navigation system. The vehicle navigation system may include a navigation sensor mounted to the frame structure, and a processor in communication with the navigation sensor. The navigation sensor may be configured to detect reference elements disposed in or on a road on which the vehicle travels. The processor may be configured to receive, from the navigation sensor, signals indicative of a sequence or pattern of detected reference elements. The processor may also be configured to determine, using the received signals, at least one of a position, velocity, or orientation of the vehicle on the road.

Disclosed herein are system, method, and computer program product embodiments for switching between local and remote guidance instructions for autonomous vehicles. For example, the method includes, in response to monitoring one or more actions of objects detected in a scene in which the autonomous robotic system is moving, causing the autonomous robotic system to slow or cease movement in the scene. The method includes detecting a trigger condition based on movement of the autonomous robotic system in the scene. In response to the one or more monitored actions and detecting the trigger condition, the method includes transmitting a remote guidance request to a remote server. After transmitting the remote guidance request, the method includes receiving remote guidance instructions from the remote server and causing the autonomous robotic system to begin operating according to the remote guidance instructions.

Disclosed herein are system, method, and computer program product embodiments for switching between local and remote guidance instructions for autonomous vehicles. For example, the method includes, in response to monitoring one or more actions of objects detected in a scene in which the autonomous robotic system is moving, causing the autonomous robotic system to slow or cease movement in the scene. The method includes detecting a trigger condition based on movement of the autonomous robotic system in the scene. In response to the one or more monitored actions and detecting the trigger condition, the method includes transmitting a remote guidance request to a remote server. After transmitting the remote guidance request, the method includes receiving remote guidance instructions from the remote server and causing the autonomous robotic system to begin operating according to the remote guidance instructions.

A sensor system for a construction machine, in particular a road finishing machine, includes a laser scanner and an evaluation unit. The laser scanner can be arranged on the construction machine or the road finishing machine itself and is configured to search a specified angular range for objects and to determine angles of the specified angular range according to distance values describing the distance to the one or several objects together with corresponding intensity values describing an intensity of a reflection resulting at the one or several objects. The evaluation unit is configured to detect an object as a reference together with corresponding angles based on a known pattern including the distance values and the intensity values across the angles. Further, the evaluation unit is configured to determine a distance to the reference and/or an angle with respect to the reference.

The invention relates to a vehicle chassis (6) for checking and/or counting stock (4) in a warehouse (3) and configured for attaching to an autonomous indoor vehicle (9), with an extendable mast (11) comprising a first end (12) mounted onto the chassis (6) and an opposite second end (13) arrangeable at different distances above the chassis (6), and at least one scanner (2) arranged at the second end (13) and configured for checking and/or counting stock (4) in a shelve (5) of the warehouse (3) lateral to the vehicle (1). The invention further relates to an autonomous robot vehicle (1) comprising the vehicle chassis (6) and the autonomous indoor vehicle (9), whereby the chassis (6) is mounted onto the autonomous indoor vehicle (9) such that the autonomous indoor vehicle (9) and the chassis (6) are configured for autonomously moving the vehicle (1) in the warehouse (3).

A controller of a machine determines jointly a sequence of control inputs defining a state trajectory of the machine and a desired knowledge of the environment by solving a multivariable constrained optimization of a model of dynamics of the machine relating the state trajectory with the sequence of control inputs subject to a constraint on admissible values of the states and the control inputs defined based on the desired knowledge of the surrounding environment represented by the state of the environment and the uncertainty of the state of the environment determined from the measurements of the environment. In such a manner, the controller performs joint but imbalance optimization of the control inputs and the sensing instructions to the sensor for learning the environment.

A controller of a machine determines jointly a sequence of control inputs defining a state trajectory of the machine and a desired knowledge of the environment by solving a multivariable constrained optimization of a model of dynamics of the machine relating the state trajectory with the sequence of control inputs subject to a constraint on admissible values of the states and the control inputs defined based on the desired knowledge of the surrounding environment represented by the state of the environment and the uncertainty of the state of the environment determined from the measurements of the environment. In such a manner, the controller performs joint but imbalance optimization of the control inputs and the sensing instructions to the sensor for learning the environment.

Systems and methods for detecting blind spots using a robotic apparatus are disclosed herein. According to at least one exemplary embodiment, a robot may utilize a plurality of virtual robots or representations to determine intersection points between extended measurements from the robot and virtual measurements from a respective one of the virtual robot or representation to determine blind spots. The robot may additionally consider locations of the blind spots while navigating a route to enhance safety, wherein the robot may perform an action to alert nearby humans upon navigating near a blind spot along the route.

A hybrid modular storage fetching system is described. In an example implementation, the system may include a warehouse execution system adapted to generate a picking schedule for picking pick-to-cart and high-density storage items, and an AGV dispatching system adapted to dispatch a cart automated guided vehicle and a modular storage fetching automated guided vehicle based on the picking schedule. The cart automated guided vehicle may be adapted autonomously transport a carton through a pick-to-cart area and to a pick-cell station. The modular storage fetching automated guided vehicle may be adapted to synchronously autonomously transport a modular storage unit containing items to be placed in the cartons from a high-density storage area to the pick-cell station.