Systems for managing access to an autonomous vehicle includes an autonomous vehicle including a plurality of storage compartments, wherein each of the plurality of storage compartments comprises a locking mechanism and at least one processor to receive data associated with an item to be positioned in a storage compartment of the plurality of storage compartments, determine that one of the plurality of storage compartments has storage capacity for the item, designate one of the plurality of storage compartments for storage of the item, activate the locking mechanism of the designated storage compartment to lock the designated storage compartment after the item is positioned in the designated storage compartment, and activate the locking mechanism of the designated storage compartment to unlock the designated storage compartment to allow removal of the item from the designated storage compartment. Methods, computer program products, and autonomous vehicles are also disclosed.

Described herein are various systems and processes for vehicles for delivery of real-time, on-demand orders for perishable goods, and operations thereof. The automated delivery vehicle may include a food transport container and various sensors configured to determine the location and/or surroundings of the vehicle. The automated delivery vehicle may further include a display and/or other output source configured to provide outputs to persons surrounding the automated delivery vehicle. Such outputs may include, for example, an information graphical representation (e.g., provided on a display), an audio output, and/or data communicated to a wireless device.

Disclosed are systems and methods for dynamically re-routing a pick path to an alternate pick location in response to identifying a shorted product at a pick location. The dynamic decision to re-route an autonomous vehicle is based on completion scores representing a likelihood of completing order in an autonomous vehicle, a maximum remaining time, an additional pick time, and order priorities. Based on various weights for factors of the orders, a system may re-route the autonomous vehicle to fulfill a shorted order at an alternate location when no orders have a high likelihood of completion, the additional pick time associated with re-routing the autonomous vehicle to the alternate pick location is less than the maximum remaining time for each order on the autonomous vehicle, and/or none of the orders on the autonomous vehicle have a higher priority than the shorted order.

A deployment mechanism and a delivery container enabling unattended delivery of cargo by a vehicle navigating autonomously on both vehicle lanes and pedestrian ways. A trailer for an autonomous vehicle for hauling additional cargo and power supplies. A method for delivering and picking up goods using delivery trucks, autonomous vehicles, and trailers. The deployment mechanism can include a crane, a robot arm, a forklift, straps, and sails. The delivery container can include visible, partly visible, or hidden security features and grasping features, and can be foldable and stackable. The trailer can include a 4-bar linkage, the 4-bar linkage enabling consistent pitch between the trailer cargo and a cargo hold of the towing vehicle. The trailer wheels are decoupled from the 4-bar linkage, connected by swing arms and possible shock absorbers. The trailer can buffer fore/aft movement of the trailer.

A mobility for storing a personal transportation includes a first storage unit formed on a side of the mobility and configured for storing the personal transportation therein without folding thereof; a second storage unit formed on a side of the mobility and configured for storing the personal transportation therein after the personal transportation is folded; a controller configured to control the first storage unit and the second storage unit in response to a mobility user's request; and a server configured to receive information related to whether the first storage unit and the second storage unit are used, and a remaining battery capacity, use time, and movable distance of the stored personal transportation from the controller, and to communicate with the mobility user.

An article management system utilizes an electric cart which may autonomously move, automatically and easily managing articles and ensuring the convenience of delivery service by the automation of article delivery.

Postal, package, and grocery deliveries are performed routinely everywhere around the world. Currently, the delivery truck drives slowly, and the postman or delivery man goes from one house to another. The postman already has a box that he carries with the sorted letters for a few of the contiguous houses, stops the truck, and walks to the different houses in the bunch, and then moves the truck and goes to the next bunch of houses. In this invention, the package delivery truck will automatically follow the mailman while still staying close to the curb to minimize traffic issues. Here, the autonomous package or delivery truck could actually go in front of the mailman to look for a good spot for the next cluster, or can wait for the mailman that is close to the last house of the current cluster, pick him up, and drop off at the center of the next cluster, or at the first house of the next cluster. In addition, there are robots that replace the function of the human (mailman or grocery delivery man).

A transportation system controls a fleet of autonomous vehicles to implement passenger transportation and coordinate delivery of baggage or other associated items using separate vehicles. The transportation system receives passenger data and associated item data via a user interface, and determines the number and type of autonomous vehicles to transport the passengers and items from selected pick-up locations to a destination. In various implementations, the transportation system may support different pick-up locations, pick-up times and/or delivery times for the passengers and associated items. The transportation system also may determine delayed item delivery options for different delivery times and modes of transportation. Based on the passenger and item data, along with input received via the user interface, the transportation system determines the vehicles to deploy and the delivery routes, and transmits instructions to the autonomous vehicles to provide the passenger transportation and perform the item delivery.

Systems and methods for predicting a trajectory of a moving object are disclosed herein. One embodiment downloads, to a robot, a probabilistic hybrid discrete-continuous automaton (PHA) model learned as a deep neural network; uses the deep neural network to infer a sequence of high-level discrete modes and a set of associated low-level samples, wherein the high-level discrete modes correspond to candidate maneuvers for the moving object and the low-level samples are candidate trajectories; uses the sequence of high-level discrete modes and the set of associated low-level samples, via a learned proposal distribution in the deep neural network, to adaptively sample the sequence of high-level discrete modes to produce a reduced set of low-level samples; applies a sample selection technique to the reduced set of low-level samples to select a predicted trajectory for the moving object; and controls operation of the robot based, at least in part, on the predicted trajectory.

Disclosed is a mobile robot. The mobile robot may include a body and a controller. The mobile robot may execute an artificial intelligence (AI) algorithm and/or a machine learning algorithm, and may perform communication with other electronic devices in a 5G communication environment. Accordingly, user convenience can be significantly improved.