Abstract: An autonomous robot with a modular conveyor belt moves materials in a warehouse or other industrial environment. Example embodiments may include systems and methods for autonomous robots with conveyor systems. An example method may include detecting, by an autonomous cart, an unloading station, moving to a position at or near the unloading station, and determining, using a first load cell, a first position of a first item on a conveyor belt of the autonomous cart. Some methods may include determining a length of time for which to actuate the conveyor belt based at least in part on the first position, and causing the conveyor belt to unload the first item from the autonomous cart by actuating the conveyor belt for the length of time.

Abstract: Systems and methods are disclosed for holonomic drivetrain modules for mobile robots. In one embodiment, an example mobile robot may include a chassis, and a holonomic drivetrain module removably coupled to the chassis. The holonomic drivetrain module may include a first drive wheel having a caster angle of substantially zero, a first bearing block assembly vertically aligned with the first drive wheel, and a first steer motor coupled to the first bearing block assembly and vertically aligned with the first drive wheel.

Abstract: Systems, methods, and computer-readable media are disclosed for universal anchor points for mobile robots. In one embodiment, an example mobile robot may include a chassis, a removable assembly comprising a support member, and a first anchor point coupled to the chassis. The first anchor point may be configured to anchor the support member to the chassis. The first anchor point may be configured to be coupled to support members of different diameters or widths.

Abstract: An autonomous cart moves products and materials in an industrial environment. It is different from conventional carts because it can navigate autonomously indoors or outdoors in dynamic environments where things change frequently. This autonomous cart uses state-of-the-art “dense” visual perception giving it unequalled and continuous awareness of its surroundings. With this it can operate at a cost, speed, level of safety and efficiency that has never been possible before. This robotic cart makes factories and warehouses more efficient and safer. It enables the movement of smaller batches of material more frequently, reduces the need for expensive conveyor systems, and helps eliminate dangerous and polluting fork trucks from indoor environments.

Abstract: An autonomous robot with a modular conveyor belt moves materials in a warehouse or other industrial environment. Its load cells detect items on its conveyor belt and its cameras detect loading stations with stationary conveyor belts throughout the warehouse. It guides itself to a loading station using visual cues until it is close enough to load or unload items from its conveyor belt. The cart orients itself relative to the stationary conveyor belt based on the conveyor belt's direction of motion and tracks its position using wheel or visual odometry. It unloads by running the conveyor belt, which may be about 1.5 m long, at a speed of about 1 m/s for about 2 seconds. For loading, the cart detects an item on a stationary conveyor belt using a camera, positions itself next to the stationary conveyor belt, then triggers the stationary conveyor belt and its own conveyor belt to load the item.

Abstract: Systems, methods, and computer-readable media are disclosed for universal anchor points for mobile robots. In one embodiment, an example mobile robot may include a chassis, a removable assembly comprising a support member, and a first anchor point coupled to the chassis. The first anchor point may be configured to anchor the support member to the chassis. The first anchor point may be configured to be coupled to support members of different diameters or widths.

Abstract: An autonomous cart moves products and materials in an industrial environment. It is different from conventional carts because it can navigate autonomously indoors or outdoors in dynamic environments where things change frequently. This autonomous cart uses state-of-the-art “dense” visual perception giving it unequalled and continuous awareness of its surroundings. With this it can operate at a cost, speed, level of safety and efficiency that has never been possible before. This robotic cart makes factories and warehouses more efficient and safer. It enables the movement of smaller batches of material more frequently, reduces the need for expensive conveyor systems, and helps eliminate dangerous and polluting fork trucks from indoor environments.

Abstract: An autonomous robot with a modular conveyor belt moves materials in a warehouse or other industrial environment. Its load cells detect items on its conveyor belt and its cameras detect loading stations with stationary conveyor belts throughout the warehouse. It guides itself to a loading station using visual cues until it is close enough to load or unload items from its conveyor belt. The cart orients itself relative to the stationary conveyor belt based on the conveyor belt's direction of motion and tracks its position using wheel or visual odometry. It unloads by running the conveyor belt, which may be about 1.5 m long, at a speed of about 1 m/s for about 2 seconds. For loading, the cart detects an item on a stationary conveyor belt using a camera, positions itself next to the stationary conveyor belt, then triggers the stationary conveyor belt and its own conveyor belt to load the item.

Abstract: The disclosure provides systems and methods of use pertaining to a visual mapping and transportation management system for determining a location of a user and directing a vehicle to the user's location. Embodiments include a navigation application installed upon a user's mobile computing device and configured to transmit a user image from the device to an image-matching server storing a map composed of keyframes, each having a stored image, a known geometric pose, and numerous extracted interest features. The server also includes a processor configured to extract interest features from the user image, compare the interest features between the user image and the stored images, identify common interest features between the two, and based on the common interest features and known geometric poses of the stored images, determine a global geometric pose of the user image before directing the vehicle to the user's location. Other embodiments are also disclosed.

Abstract: The disclosure provides systems and methods of use pertaining to a visual mapping and transportation management system for determining a location of a user and directing a vehicle to the user's location. Embodiments include a navigation application installed upon a user's mobile computing device and configured to transmit a user image from the device to an image-matching server storing a map composed of keyframes, each having a stored image, a known geometric pose, and numerous extracted interest features. The server also includes a processor configured to extract interest features from the user image, compare the interest features between the user image and the stored images, identify common interest features between the two, and based on the common interest features and known geometric poses of the stored images, determine a global geometric pose of the user image before directing the vehicle to the user's location. Other embodiments are also disclosed.