A rover or semi-autonomous or autonomous vehicle may use an image classifier to determine a terrain class of regions of an image of the terrain ahead of the rover or vehicle. The regions of the images are used to estimate the slope of the terrain for the different regions. The terrain class and slope are used to predict an amount of slip the rover will experience when traversing the terrain of the different regions. A heuristic mapping for the terrain class may be applied to the predicted slip amount to determine a hazard level for the rover or vehicle traversing the terrain.

A vehicle moves through an environment (e.g., a farming, construction, mining, or forestry environment) and performs one or more actions in the environment. Portions of the environment may include moisture, such as puddles or mud patches. A control system associated with the vehicle may include a traversability model or a moisture model to help the vehicle operate in the environment with the moisture. In particular, the control system may employ the traversability model to reduce the likelihood of the vehicle attempting to traverse an untraversable portion of the environment, and the control system may employ the moisture model to reduce the likelihood of the vehicle performing an action that will damage a portion of the environment.

A robot assembly for safe operation in a manufacturing setting with humans including a sensor for detecting a human location and human movement is provided. A safety control module providing a boundary of a safety zone area that is associated with the human in a task oriented state that includes a largest possible area in which the human or an associated work object can extend when the human is standing in one location and performing the work task. The human movement and safety zone area location being used to develop a capture set area that includes at least one predictive future safety zone area location. Using the at least one predicted future safety zone area, establishing a travel path for moving the robot between locations without overlapping the capture set area.

In an apparatus for determining a traveling position of an own vehicle that is an autonomous driving vehicle equipped with the apparatus, a judgment section is configured to judge presence or absence of at least one of a travel history of other vehicles regarding the lane in which the own vehicle is traveling and an object that is located in the vicinity of the own vehicle within the lane in which the own vehicle is traveling and should be avoided coming into contact with. The traveling position is a widthwise position of the own vehicle within a lane in which the own vehicle is traveling. A determination section is configured to determine the traveling position using the travel history in response to the judgment section judging that the travel history exists and using position information of the object in response to the judgment section judging that the object exists.

An autonomous vehicle safety system may activate to prevent collisions by detecting that a planned trajectory may result in a collision. If the safety system is overly sensitive, it may cause false positive activations, and if the system isn't sensitive enough the collision avoidance system may not activate and prevent a collision, which is unacceptable. It may be impossible or prohibitively difficult to detect false positive activations of a safety system and it is unacceptable to risk a false negative, so tuning the safety system is notoriously difficult. Tuning the safety system may include detecting near-miss events using surrogate metrics, and tuning the safety system to increase or decrease a rate of near-miss events as a stand-in for false positives.

Aspects described herein include an autonomous surface vehicle (ASV) for operation within an inventory system of an environment. The ASV includes a drive system, a docking system, a plurality of sensors, and a memory storing a map of the environment. The ASV further includes one or more computer processors configured to (i) detect, using a location sensor, a location of the ASV within the environment; (ii) control the drive system to actuate the ASV toward a corridor defined in the map at a first speed setting; and control the drive system to actuate the ASV through the corridor along at least one barrier defined in the map. A second, greater speed setting is applied when (i) the location sensor indicates that the ASV is within the corridor and (ii) one or more fiducials along the at least one barrier are visually detected by one or more proximity sensors.

A guide-type virtual wall system is provided. The system comprises a beacon (11, 44) and a robot (12), wherein a transmission module of the beacon (11, 44) directionally transmits a first signal, and an area covered by the first signal defines a beacon signal area (13). The robot (12) comprises a beacon signal receiving module corresponding to the beacon signal transmission module. When the robot (12) enters the beacon signal area (13) and the beacon signal receiving module detects the first signal, the robot (12) advances towards the direction of the beacon (11, 44) until it detects a second signal, and then the robot (12) crosses over or exits from the beacon signal area (13). The system can restrict the robot (12) from entering a certain area, wherein the area where a virtual wall is located is not missed, and the robot (12) is also enabled to cross over the virtual wall to enter the restricted area when required.

Aspects of the disclosure relate generally to controlling an autonomous vehicle in a variety of unique circumstances. These include adapting control strategies of the vehicle based on discrepancies between map data and sensor data obtained by the vehicle. These further include adapting position and routing strategies for the vehicle based on changes in the environment and traffic conditions. Other aspects of the disclosure relate to using vehicular sensor data to update hazard information on a centralized map database. Other aspects of the disclosure relate to using sensors independent of the vehicle to compensate for blind spots in the field of view of the vehicular sensors. Other aspects of the disclosure involve communication with other vehicles to indicate that the autonomous vehicle is not under human control, or to give signals to other vehicles about the intended behavior of the autonomous vehicle.

A system for determining and executing an autonomous-vehicle vehicle travel route, including a hardware-based processing unit and a non-transitory computer-readable storage medium. The storage medium includes an input-interface module that, when executed by the hardware-based processing unit, obtains factor data indicating factors relevant to determining a vehicle travel route. The storage medium also includes a route-generation module comprising a route-complexity sub-module. The route-complexity sub-module determines, based on the factor data, route-complexity indexes corresponding to respective optional routes. The route-generation module determines the vehicle travel route based on the route-complexity indexes. The storage in various embodiments includes other sub-modules associated with other elements, such as autonomous-driving safety, comfort, stress, pollution, scenery, or infrastructure-accessibility, for determining and executing an autonomous-driving travel route. In some embodiments, the storage includes an autonomous-driving perceptions module and an autonomous-driving control module for modifying vehicle functions in executing the autonomous-driving travel route.

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.