Amazon Technologies, Inc.

Stephen Charles Paschall

Dincer Bozkaya

John Joseph Enright

Matthew Anthony Brady

Justin Croyle

Adam Joseph Greenbaum

Fahrudin Alagic

Christopher John Schuchmann

Eric Jones

Rakesh Mishra

Systems and methods are disclosed for automated force feedback detection for autonomous robots transporting containers. In one embodiment, an example mobile robot is configured to transport a container. The mobile robot can include a first sensor, a second sensor, a motor, and a controller. The controller may be configured to determine that the container is loaded, determine, using at least one of the first sensor and the second sensor, that a first change in load distribution along a first axis satisfies a threshold, determine that the first change in load distribution has persisted for a first length of time, and cause the motor to be disabled.

Automated force feedback detection for autonomous robots transporting containers

Systems and methods to test autonomous mobile robots (AMRs) may include a dynamometer, a robotic system carrying an object, and a control system. An AMR under test may be positioned on the dynamometer and instructed to perform navigation maneuvers, which may be detected by the dynamometer. The control system may receive the detected movements and determine corresponding movements for the robotic system using inverse kinematics. Then, the control system may instruct movement of the object via the robotic system based on the corresponding movements. Using such test systems and methods, perception systems and responses by safety, navigation, and/or drive systems of AMRs may be tested in a controlled, robust, and repeatable manner.

Systems and methods to test perception and safety responses of autonomous mobile robots

Disclosed are various embodiments for optimizing robot utilization in autonomous mobile robots by accounting for the battery charge state when assigning missions to be performed by the autonomous mobile robots in a material handling facility. In particular, mission data associated with one or more missions and robot data including a battery charge state associated with one or more robots can be analyzed to determine a robot mission assignment that accounts for battery state charge in order to maximize robot utilization and productivity of material handling tasks.

Battery charge state based mission assignment for autonomous mobile robots

An inventory management system can include a fleet of mobile drive units. The mobile drive units can detect, using a sensor, calibration data associated with a calibration fixture. The calibration of the sensors can be updated based on the calibration data. The calibration data for the fleet of mobile drive units can be used determine a correction factor. The correction factor can be applied to the fleet of mobile drive units to further update the calibration of the sensors.

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Acton, MS, United States of America

Stephen Charles Paschall