Novel Dynamic Vehicle Scheduling and Path Planning Algorithms for Mobile Robotic and AGV Warehouse Order Picking

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Factory automation separates robots from operators. Developing soft robotics enables humansto work in close collaboration with Automated Mobile Robot’s (AMR’s), leveraging ahumans full manipulative & decision-adaptive skills. Scheduling AMR movement in areasalso occupied by humans provides a key component in this capability. The projectrequirement is driven by 10 yrs of massive growth in internet shopping that has had a hugeimpact on the assembly of small orders & with multi-channel selling has profoundly affectedwarehouse design. Order picking is usually the highest active cost element behind the passivecost of inventory. The need for efficiency & accuracy is driving the sector to various forms ofpick automation. Industry experts expect future solutions to be vision guided, robotic piecepicking & shuttles roaming a facility to make a delivery in an environment where automatedmaterials handling, robotics & humans intermingle. This can only be fully realised ifappropriate scheduling systems are developed. The 12 month project aims to prove thetechnical feasibility of a highly novel dynamic AMR scheduling solution, capable ofoptimising the schedule of a large fleet (>50) of AMR’s operating in a soft roboticsenvironment. The project will develop the schedule control algorithms & demonstrate thefeasibility in both a controlled work space & in a small representative end user trial. Thescheduling solution will optimise the route of a large fleet of AMR’s so the time of travel foreach order is minimised while its timed arrival at the picking locations minimises the distancewalked between picking points by the operator, while also ensuring no vehicle collisions &minimum waiting times.Guidance has engaged with an innovative high growth distribution business to provide enduserinsight & representative trial facilities & is utilising specific schedule algorithm expertisefrom the University of Birmingham School of Computer Science as sub-contractors.