Speaker
Description
Automated guided vehicles (AGVs) are an essential
area of research for the industry to enable dynamic transport
operations. Furthermore, AGV-based multi-robot systems (MRS)
are being utilized in various applications, e.g. in production or in
logistics. Most research today focuses on ensuring that the system
is operational, which is not always achieved. In daily use, faults
and failures in an AGV-based MRS are most likely inevitable.
So industrial systems must support some safety methods, e.g. an
emergency stop function. Although emergency stop functions are
designed to prevent larger issues, their usage leads to a failure of
the control system, since the affected systems are typically shut
down immediately. Depending on the AGV type, an uncontrolled
behaviour can occur. In case of control failure, this behaviour
can lead to collisions and associated high costs. In this paper, we
present and compare three approaches for avoiding collisions in
an intralogistics scenario in the case of control failure. In the said
scenario, the trajectory planing is being adapted to minimize or
avoid collisions. The first approach calculates the next collisionfree
time slot when an emergency stop occurs and continues the
planned trajectories until this time. The second approach calculates
several alternative trajectories with the existing trajectory
planning without considering emergency stop collisions. The third
approach aims to completely avoid emergency stop collisions
by extending trajectory planning to include the detection of
possible emergency stop collisions. We evaluate and compare
the approaches by employing multiple metrics to assess their
performance, including runtime, number of collisions that occur,
and the system’s throughput. We thoroughly discuss and analyse
the results, offering insights into the strengths and weaknesses
of the approaches.
| Type of presentation | Invited Talk |
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