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
Transcript of 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
• 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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Markus Boehning
SICK AG, Central Unit Research
MANY THANKS FOR YOUR ATTENTION.
