KIVA system

COORDINATING HUNDREDS Automation and Control Seminar 1

OF COOPERATIVE,
AUTONOMOUS VEHICLES IN
A WAREHOUSE

Dev Bahadur Poudel
Automation and Control Seminar
Jacobs University
Bremen

Monday, July
30, 2012

Structure of Presentation
2

 Overview on Multi-Agent System
 Multi Agent System in Warehouse
 Kiva System in Warehouse

Automation and Control Seminar Monday, July 30, 2012

Autonomous Robot
3

 Robots that can perform desired task in
unstructured environment without human
guidance.
 Have some degree of autonomy
 Have control over their internal state and their
behavior


Agents
4

 Computer system that is capable of
independent(autonomous) action to satisfy
design objectives
 Problem Solving entities
 Situated in a particular environment (input
environment through sensors and act on
environment through effectors)


Multi-Agent System
5

 Agent Oriented Approach to solve Complex
Problem
 Consist of a number of agents interacting with
each other to accomplish the goal in a
common environment
 Problem are decentralized to different agents
 Decomposition of Knowledge and Expertise
 Distributed Intelligence


Why and Where Multi-agents
6
Systems?
 Decentralization of Problems and Knowledge
 For Complex Control Systems
 Increase the productivity and decrease the
cost
 Reliability, Robust
 Military Network-centric Operations
 Search and Rescue
 Transportation and Logistics
 Now days used in Warehouse to increase the
efficiency

Warehouse Scenario
7

 Goods-to- Customer


Traditional Automation in
8 Warehouse
 Pickers(human) move around the Warehouse
 Fetch products and return them to packing
station
 Human have to look for the order items
 Order items in Conveyors
 Batch Processing
 Time consuming


Modern Automation in
9
Warehouse
 Orders’ item come in hand of picker like a
MAGIC!
 Use of Autonomous agents
 Agents search the order fetch to the human
 Agents co-ordinate to achieve a system goal
 Many orders can be fulfilled
 Increases Productivity
 Kiva System


Kiva System
10

 State-of-the art for modern automation in
warehouse
 Founded on better approach for order fulfillment
(goods to customers)
 Uses Hundreds of autonomous mobile robots
 Sophisticated control Software
 Uses the concept of Distributed Intelligence
 Founded in 2003 (Mick Mountz )
 Fielded in 2006
 Implements Distributed Intelligence

Resources
11

 Inventory ( with dimensions and frequency)
 Inventory Pods (pods can visit one or multiple
stations)
 Bins (pods can have 1-1000 bins)
 Order Pods
 Parking space for pods
 Robots
 Picking Stations


Kiva System Layout
12

 Green: Storage Area
 Orange: Mobile Robots
 Blue: Stations

MAS Architecture in
Warehouse(Kiva)
13

Agent 1 Job Manager

Inventory Station Drive Unit

Agent 2 Agent 3


Drive Unit Agent
14

 Mobile Robots
 Fetch the Inventory pod to the picking station
 Take the Order pods to the shipping station
 Transport the Inventory Pod to replenishment
 Path Planning


15
Inventory Station Agent(ISA)
 Picking stations : Workers pick items
 Replenishment stations: barcodes are
scanned and appropriate pod come to the
station
 Report accomplishment of its tasks.
 Equipped with computer that pick lights,
barcode scanners, laser pointers used to
identify the pick and put locations


Job Manager
16

 Central Server System
 Resource Allocation
 Communicate with Warehouse Management
System
 Receives customer orders that need to be
fulfilled
 Assigns drives, pods, and stations to carry out
the tasks.


Kiva Robots and Pods
17


Kiva working Mechanism
18

 JM receives orders and assign to stations to
fulfill
 Robot(Drive Unit) carries the inventory pods
 Inventory pods come to picking stations
 Picking: Workers pick items and put in order
pod
 Shipping : Order pod move for shipping after
fulfilling all the orders
 Replenishment : Inventory pods go for
replenishment Automation and Control Seminar Monday, July 30, 2012

19
Order fetch Configuration


Path Planning
20

 Optimization of the path to fetch order from
storage to the station
 A* Algorithm
 Travelling Salesman Problem


21
Resource Allocation Challenges
 Objective: Optimizing the system(keep the
workers busy minimizing the robots and pods
used)
 Which order to assign to which robot?
 Which pod to pick up?
 Where to keep the pod after order is fulfilled?
 Which pod to send for replenishment?
 Optimization(make all the robots and stations
busy)

Heuristic Technique for
22 Optimization
 Order Allocation
1.Time to fulfill the order must be minimized
2. Inventories around the station and in
queue pods must be considered
 Inventory Pod Selection
1.Nearer pods
2. Multiple items to be picked in one visit


Resource Allocation
23

 Pod Storage Allocation:
1.Slow frequency pods kept backward
2.high frequency pods are kept nearer
 Robot Allocation:

1.Pick More pods using less Robots
2.Decrease the Queue in stations
 Replenishment Allocation:

1.Maximize the cubic utilization of the pods
2.Bin packing Problem
3.Create faster pods and slower pods


Advantages
24

 Increase Productivity: double the output
 Lower Cost: lower installation and operational
costs than traditional warehouse automation
systems
 Location free replenishment : items can be
kept in any pods
 Adaptive storage: Pods are store using
heuristic
 Expandability :Add inventory pods and drive
units to increase throughput during peak2012
Automation and Control Seminar Monday, July 30,
season

Challenges
25

 To the Computer Scientist
 Development of an appropriate high level
software infrastructure/framework to support
the building of multi-agent systems
 Efficient Algorithm for Optimization
 Path Planning for robots
 Resource Allocation
 Coordinating Robots
 Dynamic, Stochastic and hence Intractable


Kiva in Action
26


27

Have a Nice Day!


KIVA system

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