robust localisation of automated guided vehicles in...

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ROBUST LOCALISATION OF AUTOMATED GUIDED VEHICLES IN DYNAMIC LOGISTICS ENVIRONMENTS

Markus Boehning

SICK AG, Central Unit Research

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IT‘S ALL ABOUT LOCALIZATION AND SAFETY MOTIVATION FOR AUTOMATED GUIDED VEHICLES

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DEL MONTE PLANT EXAMPLE OF AUTOMATED WAREHOUSE LOGISTICS

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LOCALISATION APPROACHES FOR AGVS REQUIREMENTS AND SOLUTIONS

Track-/Grid-based navigation • Applications with simple or predefined paths

Reflector-based localisation • Applications with free and ad hoc planned paths

• Uses navigation sensors such as SICK NAV350

• High installation efforts and costs for artificial landmarks

Contour-based localisation • Applications in environments without artificial landmarks

• Either dedicated navigation laser scanner (AGV) or

reuse of safety laser scanner data (AGC)

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SMART MICRO FACTORY FOR E-CARS WITH LEAN PRODUCTION PLANNING SMART FACE

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CONTOUR-BASED LOCALISATION IN SMART FACE DEMONSTRATORS

Contour-based localisation using Monte-Carlo localisation (MCL)

SICK S300 Shopfloor-Demonstrator

SICK TiM5xx Minidemonstrator

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CONTOUR-BASED LOCALISATION APPROACH AND CHALLENGES

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CONTOUR-BASED LOCALISATION APPROACH AND CHALLENGES

• Mobile objects are not registered in the digital environment map

• Low accuracy or failure of the MCL

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LOCALISATION IN DYNAMIC ENVIRONMENTS UPDATE OF THE REFERENCE MAP

• Contour-based localisation using MCL

approach

• Evaluation of pose accuracy based on

Measurement/outlier ratio

Variance of position estimations

• Map update after repeated observation of

position with high accuracy

Localisation

Accuracy evaluation

Map update

yes no

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LOCALISATION IN DYNAMIC ENVIRONMENTS UPDATE OF THE REFERENCE MAP

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LOCALISATION IN DYNAMIC ENVIRONMENTS UPDATE OF THE REFERENCE MAP

• Comparison of position and angle accuracy

with dynamic map update (blue)

without dynamic map update (red)

• Ground truth reference

reflector-based laser localisation (NAV350)

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OUTLOOK INFORMATION EXCHANGE BETWEEN VEHICLES

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Markus Boehning

SICK AG, Central Unit Research

markus.boehning@sick.de

MANY THANKS FOR YOUR ATTENTION.