Amazon Technologies, Inc.

Stephen Caldara

Robert Michael Shydo, Jr

Andrew Stubbs

Gregory Edward Tierney

Matthew David Verminski

Fahrudin Alagic

Dincer Bozkaya

Ashish Shah

Seth Kaufman

Gregory Cartagena

Sara Jean Woo

Jing Ma

Jianfeng Pu

William Joseph Klein

Peter K Mansfield

Gabriel Hebert

Justin Croyle

Albert William Saunders, Iv

Olugbenga Osibodu

Karl Bernard Swanson

Robert Michael Shydo

Systems and techniques for performing a calibration test of an obstacle detection sensor of a drive unit are described. An example system includes a calibration region and at least one drive unit. The calibration region is disposed in an environment and includes a calibration apparatus. The at least one drive unit is operable to autonomously move throughout the environment. The at least one drive unit includes a sensor configured to detect one or more objects within the environment. The at least one drive unit is configured to autonomously transition to the calibration region upon detecting at least one predetermined condition, and perform a calibration test of the first sensor at the calibration region using the calibration apparatus.

Calibration garage for automated calibration of depth sensors in mobile robots

Systems and methods for evaluating the performance of three-dimensional (3D) sensors can include, for example, obtaining, via a 3D sensor in a testing apparatus, range information of a scene within a field-of-view (FOV) of the 3D sensor. The scene includes a plurality of targets disposed within the testing apparatus. Each of the plurality of targets is located at a different distance from the 3D sensor in the testing apparatus. A validation of the performance of the 3D sensor at the different distances is performed at a same point in time, based on the range information. An indication of a result of the validation is provided.

Three-dimensional (3D) sensor performance evaluation

Techniques for providing a signal processing feature in an inventory management system are described herein. For example, instructions may be received by a computer system of an autonomous vehicle that identify a path to move inventory within a materials handling facility. Further, the computer system of the autonomous vehicle may reduce a current traveling speed of the autonomous vehicle in response to receiving a first signal that is provided by a transmitter coupled with an entity moving within the materials handling facility. The first signal may be span a first distance. In embodiments, the computer system of the autonomous vehicle may stop movement of the autonomous vehicle in response to receiving a second signal provided by the transmitter coupled with the entity. The second signal may span a second distance from the entity that is less than the first distance.

AGV traffic management system

Techniques described herein include a system and methods for implementing fast motion planning of collision detection. In some embodiments, an area voxel map is generated with respect to a three-dimensional space within which a repositioning event is to occur. A number of movement voxel maps are then identified as being related to potential repositioning options. The area voxel map is then compared to each of the movement voxel maps to identify collisions that may occur with respect to the repositioning options. In some embodiments, each voxel map includes a number of bits which each represent voxels in a volume of space. The comparison between the area voxel map and each of the movement voxel maps may include a logical conjunction (e.g., an AND operation). Movement voxel maps for which the comparisons result includes a value of 1 are then removed from a set of valid repositioning options.

Fast motion planning collision detection

Techniques for providing an entity monitoring safety feature in an inventory management system are described herein. For example, instructions may be received by a computer system of an autonomous vehicle that identify a path to move inventory within a materials handling facility. Further, the computer system of the autonomous vehicle may reduce a current traveling speed of the autonomous vehicle in response to receiving a first signal that is provided by a transmitter coupled with an entity moving with the materials handling facility. The first signal may be provided up to a first distance from the entity. In embodiments, the computer system of the autonomous vehicle may stop movement of the autonomous vehicle in response to receiving a second signal provided by the transmitter coupled with the entity. The second signal may be provided up to a second distance from the entity that is less than the first distance.

A robot equipped with an object detection system and an object identification system is used to move inventory holders throughout a warehouse or other environment. The robot can detect objects in its path using the object detection system, which can include one or more sensors for this purpose. The robot can then classify the object using the object identification system to determine an appropriate course of action. The robot can classify the object as an inventory item, warehouse equipment, or a person, among other things. The robot can take action based on the object classification. The robot can reroute around inventory items and warehouse equipment. When encountering people or objects that cannot be classified, the robot can stop and await further instructions. In some cases, the robot may wait for a manual reset before continuing along its path.

Object avoidance with object detection and classification

Short range transmissions are used to identify potential interactions between warehouse workers and warehouse robots in automated warehouses. The robot can be equipped with one or more short range transmission tags, such as radio frequency identification (RFID) tags, while the warehouse worker can be equipped with a short range transmission reader, such as an RFID reader. The robot can detect a warehouse worker that is within range when the RFID tags on the robot are written to by the RFID reader. The warehouse robots and warehouse workers can also be equipped with one or more cameras to identify fiducials in the automated warehouse and to report their positions. A central control or interaction server can ensure that warehouse robots and warehouse workers are routed appropriately to avoid incidents.

Systems and methods to facilitate human/robot interaction

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Cambridge, MA, United States of America

Stephen Caldara