![]() ![]() A site manager must manually re-route the AGV robot to teach it a new route. A path following AGV is not able to handle these changes. In most dynamic warehouse environments, goods are moving quickly and workflow or floor plans change frequently. It could then block traffic altogether and require an operator to intervene. In this same instance, an AGV would stop because it would perceive the moving object as an insurmountable challenge. ![]() In a situation where an AMR meets oncoming traffic, it can move to the side to pass, wait until the coast is clear and then resume its mission. They are designed to share space with manually operated vehicles, other AMRs, and AGVs, and move seamlessly with other objects and entities in its shared space. Moving vehicles are a frequent feature of industrial spaces, and AMRs are much better equipped to succeed in these interactions.ĪMRs know the rules of the road. While this works in isolated incidents, it is not enough in congested areas. Dynamic Obstacle Avoidance: Passing Moving VehiclesĪGVs – or even some AMRs – employ limited obstacle avoidance, diverting for their path for only a short distance to avoid static obstacles. If this is not the most efficient choice, AMRs will choose a new route entirely. While AGVs are limited to waiting until their path is clear, AMRs can venture briefly off path to route around traffic at a safe distance, providing plenty of room for other actors to complete tasks. Robots using this technology use intelligent analytics to chose the most efficient route to complete their task, taking traffic and obstacles into consideration in real time. The path planning abilities of AMRs offer a fix to this problem, adjusting not only speed, but direction.
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