Methods, systems, and computer programs are presented for executing a mission by an autonomous device to inspect an asset. One method includes an operation for obtaining a workflow. The workflow includes operations to be executed during a mission to be performed by a robot and a destination for sending data resulting from the mission. The method further includes an operation for generating a package after completion of the mission associated with the workflow. The package is self-contained and comprises information obtained during the mission that enables generation of results. The package comprises sensor information collected by one or more sensors, telemetry information obtained by the robot, information about assets associated with the mission, software version identifier for the package generation, and routing information for transmitting the package to the destination. The method further includes an operation for analyzing the information of the package to determine results for the mission.

An example operation includes one or more of receiving, by a server, data related to an environment associated with a target transport, analyzing, by the server, the data to determine if at least one adverse condition related to the environment exists, and responsive to existence of the at least one adverse condition, sending, by the server, a recommendation related to operation of the target transport in a safe mode to overcome the at least one adverse condition to the target transport.

A system and method for improving a position accuracy of a mobile robot is disclosed. A retroreflective device is mounted to the mobile robot and used by an absolute positioning device to use a laser beam to track a position of the mobile robot. The mobile robot receives position measurements. Various optimizations may be performed to support operating the mobile robot over a 360 degree range of azimuthal headings.

A work tool system (200) comprising a work tool (100) and a server (320), the server (320) comprising a controller (321) and a communication interface (325) and the work tool (100) comprising a controller (110) and a communication interface (115), wherein the server (320) is configured to: receive movement indications for a user (U) through the communication interface (325); determine a movement pattern based on the movement indications; determine a Do Not Disturb area suitable for the movement pattern; and to transmit information on the Do Not Disturb area to the work tool (100) through the communication interface (325); and wherein the work tool (100) is configured to: receive information on the Do Not Disturb area; control the work tool so that the Do Not Disturb area is not violated.

Apparatus are provided for a sensor platform. The sensor platform includes a sensor mount adapted to receive a sensing device, and a first articulation system that has a first rotational axis. The sensor platform includes a second articulation system that has a second rotational axis, and the second rotational axis is different than the first rotational axis. The sensor platform includes a base that supports the first articulation system, the second articulation system and the sensor mount. The first articulation system and the second articulation system are independently movable to define two degrees of freedom for positioning the sensor platform.

Systems and methods are provided that may to cause autonomous navigation of autonomous vehicles in the case of non-standard traffic flows such as police stops, emergency vehicle passing, construction sites, vehicle collision sites, and other non-standard road conditions. An entity associated with the non-standard traffic flow (e.g., an emergency vehicle, road sign, barrier, etc.) may transmit or broadcast a control signal to be received (or otherwise detected) at one or more autonomous vehicles. Each autonomous vehicle, upon receiving the control signal, may autonomously navigate in accordance with the control signal, thus mitigating or eliminating dangers associated with non-standard traffic flows.

A route search system for a work vehicle includes a receiver, a processor, and a controller. The receiver is to obtain a reference position of the work vehicle. The processor is to define, as a search area, an area around a vehicle reference point in a plan view. The vehicle reference point indicates the reference position of the work vehicle. The controller is to determine a guidance travel route along which the work vehicle is to travel and which is closest to the vehicle reference point in the search area among travel route candidates stored in a memory.

This disclosure provides methods, devices and systems for a vehicle user equipment (VUE) to obtain extrinsic information about an object or location. The VUE may transmit a request for information about the object or the location to a road side unit (RSU). The RSU may receive the request and determine a set of extrinsic information for the first UE regarding the object or the location based on a set of information from one or more other UEs. The extrinsic information includes information that is not provided by the VUE. The RSU may transmit the set of extrinsic information to the VUE. The VUE may determine whether to accept a feature of the object or the location in the extrinsic information based on the set of extrinsic information and a set of intrinsic information detected by the VUE, The VUE may select an autonomous driving action based on the accepted feature.

The disclosure includes embodiments for a location data correction service for connected vehicles. A method includes receiving, by an operation center via a serverless ad-hoc vehicular network, a first wireless message that includes legacy location data that describes a geographic location of a legacy vehicle. The method includes causing a rich sensor set included in the operation center to record sensor data describing the geographic locations of objects in a roadway environment. The method includes determining correction data that describes a variance between the geographic location of the legacy vehicle as described by the sensor data and the legacy location data. The method includes transmitting a second wireless message to the legacy vehicle, wherein the second wireless message includes the correction data so that the legacy vehicle receives a benefit by correcting the legacy location data to minimize the variance.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.