Improving the human and autonomous machine collaboration through flexible route planning
In the field of autonomous work machines, growth in the coming years will be achieved by improving the cooperation between machines and humans. Mixed fleet combines the strengths of humans and robots to create a safer, more efficient, and more flexible working environment. Atostek is developing flexible and responsive route planning tailored to the needs of mixed fleets.
The term mixed fleet refers to a collaboration where human-operated work machines and autonomous work machines, such as robotic forklifts and cranes, operate together. This collaboration can reduce human errors, transfer monotonous routine tasks to robots, improve product quality, and address challenges in workforce availability.
The challenge of unpredictable human movement
How can we ensure that the collaboration between humans and machines is as safe and seamless as possible? Even minor missteps can cause chaos in the traffic arrangement of robots, necessitating flexible and quick responses to modify route plans.
Consider a practical example of an industrial warehouse, where human-driven vehicles and autonomous machines move and work. Humans adapt relatively easily to unexpected changes, while autonomous machines are highly efficient at repetitive and pre-determined tasks. Typically, the robots make detailed movement plans in advance. However, the unpredictable movements of humans can complicate the machines’ movements, such as blocking a driving route, or causing dead ends and traffic jams, which requires the robots to quickly adapt their route plans, or they will get stuck.
Predictive route planning as a tool for collaboration
Advancing the collaboration between humans and autonomous machines requires innovative solutions. One possibility is to introduce smarter route planning systems that can account for human drivers as more than just random moving obstacles.
From a route planning perspective, this means that the system must be able to track and even predict the movements of human drivers. The system must also react to unexpected situations quickly; in practice, robots’ routes or tasks must be redesigned.
Local coordination between humans and machines can be facilitated, for instance, by using machine vision to recognize hand gestures made by human operators, which can convey simple instructions to robots such as “stop, wait” or “you may proceed”. In return, robots can communicate their intentions to humans, for example, through lights, by displaying various patterns, or other gestures. Underlying this is the prerequisite that robots can immediately alter their driving plans based on the interaction.
The development of collaboration between humans and autonomous machines creates new opportunities for optimizing industrial processes, improving efficiency and job satisfaction, and increasing safety. Predictive route planning, for instance, gives human drivers greater independence in choosing their driving routes, making machines a natural tool to assist them.
Mixed Fleet Project
The Mixed Fleet project improves the collaboration between machines and humans, which accelerates the utilization of automation and increases productivity. Involved research institutions include the University of Tampere and VTT Technical Research Centre of Finland. The three-year joint project is funded by Business Finland as well as companies and research institutions.
As part of the project, Atostek is developing a new generation of comprehensive methods for route planning for groups of mobile machines.
Lauri-Tapio Korhonen
Autonomous Systems Consultant
lauri-tapio.korhonen@atostek.com
+358 44 792 4525
