A navigation system uses a dead reckoning method to estimate an object's present position relative to one or more prior positions. In some embodiments, the dead reckoning method determines a change in position from the object's heading and speed during an elapsed time interval. In embodiments suitable for use with wheeled objects, the dead reckoning method determines the change in position by measuring the heading and the amount of wheel rotation. Some or all of the components of the navigation system may be disposed within a wheel, such as a wheel of a shopping cart.

A steering assist system (SAS) for a cart is provided. The SAS may include an activation mechanism, a first actuation mechanism, a first support mechanism, a first linkage mechanism, a first stopping mechanism, and a first engagement mechanism. The first stopping mechanism may be configured to abut the first engagement mechanism to impede or prevent rotational movement of at least one wheel of the cart. The first actuation mechanism may be connected to the first linkage mechanism and the first linkage mechanism may be connected to the first stopping mechanism. The activation mechanism may be configured to activate the first actuation mechanism, causing the first linkage mechanism and the first stopping mechanism to move. The first stopping mechanism may be configured to move between a fully activated position and a fully deactivated position.

A shopping cart wheel includes a braking apparatus, clutch mechanism and electronics that control the braking apparatus in response to wireless signals. The wireless signals include low frequency electromagnetic signals within a low frequency band and high frequency signals within a high frequency band.

Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Also disclosed are various techniques to utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources. Such systems and methods can be applied in both indoor and outdoor settings and in retail or warehouse settings.

A power generation system for wheeled objects comprises a generator mechanically coupled to one or more of the object's wheels to convert wheel rotational energy into electrical energy. The power generation system may comprise an electrical storage device configured to store the electrical power produced by the generator. Power from the generator and/or the electrical storage device can be used to provide power to other electrical systems in or on the object. In certain embodiments, the electrical storage device comprises a bank of high-capacity capacitors connected in series. Some embodiments use a control circuit, for example, to regulate the charging and discharging of the capacitor bank and to provide suitable voltages for other systems. The power generation system may be disposed within an object's wheel, such as a wheel of a shopping cart.

A system for monitoring shopping carts uses cameras to generate images of the carts moving in a store. In some implementations, cameras may additionally or alternatively be mounted to the shopping carts and configured to image cart contents. The system may use the collected image data, and/or other types of sensor data (such as the store location at which an item was added to the basket), to classify items detected in the shopping carts. For example, a trained machine learning model may classify item in a cart as non-merchandise, high theft risk merchandise, electronics merchandise, etc. When a shopping cart approaches a store exit without any indication of an associated payment transaction, the system may use the associated item classification data, optionally in combination with other data such as cart path data, to determine whether to execute an anti-theft action, such as locking a cart wheel or activating a store alarm. The system may also compare the classifications of cart contents to payment transaction records (or summaries thereof) to, e.g., detect underpayment events.

The present disclosure describes a cart having an adjustable handle system, the cart having: a chassis supported on wheels; a horizontal work surface having a perimeter defined by at least a front edge, a rear edge, and two side edges; a stationary handle connected to, and extending along the perimeter of the horizontal work surface from an origination point located on the rear edge to a connecting point located on one of the two side edges; a moveable handle axially coupled to the stationary handle at the connecting point and extending along the perimeter of the horizontal work surface from the connecting point to an end point located on the front edge; and an adjustable connecting device connecting the moveable handle to the stationary handle at the connecting point and controlling the angular position of the moveable handle relative to the stationary handle.

Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Also disclosed are various techniques to utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources. Such systems and methods can be applied in both indoor and outdoor settings and in retail or warehouse settings.

A motorized shopping cart is disclosed herein and includes a shopping cart, a wheel assembly attached to the shopping cart, a drive assembly, accelerator and brake assembly in communication with the wheel assembly, a GPS module, a direction sensing module, a feedback module, a controller and in some embodiments, a collision module. The GPS module detects a location of the shopping cart relative to one or more boundaries and the direction sensing module detects a direction of travel of the shopping cart within a store. If the shopping cart moves past the boundary or in an incorrect direction of travel, the controller automatically applies the brake assembly to cease movement of the shopping cart and simultaneously causes the feedback module to vibrate at least a portion of the shopping cart. In some embodiments, if a collision is imminent, the controller activates one or more response measures for collision avoidance.

A system for monitoring shopping carts uses cameras to generate images of the carts moving in a store. In some implementations, cameras may additionally or alternatively be mounted to the shopping carts and configured to image cart contents. The system may use the collected image data, and/or other types of sensor data (such as the store location at which an item was added to the basket), to classify items detected in the shopping carts. For example, a trained machine learning model may classify item in a cart as non-merchandise, high theft risk merchandise, electronics merchandise, etc. When a shopping cart approaches a store exit without any indication of an associated payment transaction, the system may use the associated item classification data, optionally in combination with other data such as cart path data, to determine whether to execute an anti-theft action, such as locking a cart wheel or activating a store alarm. The system may also compare the classifications of cart contents to payment transaction records (or summaries thereof) to, e.g., detect underpayment events.