Etymologically, resilience is linked to the Anglo-Saxon word resilience, which designates the psychological resilience of an individual to rebuild after a shock. In physical science, the word refers to the ability of a material to withstand shocks. By analogy, resilience in robotics is the ability of the mobile robotic solution to withstand hazards/unforeseen events and to continue its activity.
The COVID-19 pandemic has fueled the need to rethink the way we work, as well as the use of new technologies. Businesses have faced the challenge of staying efficient while tackling productivity issues resulting from the outbreak. Indeed, the resilience of new technologies, in particular autonomous mobile robotics (AMR) is more than ever necessary to face current challenges.
Through this article, Fabien Benoteau, CTO* and COO* of Meanwhile, explains why autonomous mobile robots are resilient systems.
Meanwhile mobile robots are equipped with an artificial intelligence specialized in indoor navigation (SLAM). SLAM, Simultaneous Localization And Mapping, allows the robot to construct its environment and modify its behavior according to unmapped obstacles while locating itself in real time. In order to move autonomously and without a predefined trajectory, the robot will combine its own information with information from its environment (returned by its lasers and sensors).
In the event of an obstacle (operators, pallets, forklifts, etc.) obstructing its passage, the mobile robot circumvents it in complete safety, determining an alternative trajectory. Productivity is optimized because supply deadlines are more easily met.
Equipped with a charging station, Meanwhile mobile robots are able to charge independently. In order to maximize their availability, it is possible to customize the AMR reloading strategy:
Depending on the robot’s battery charge level “It corresponds to the elementary reloading process. For example, from the moment the mobile robot reaches a charge level of less than 20%, it will stop working, go to its charging station and start the recharging process in order to find an “acceptable” charge level. to return to his duties. The acceptable charge level is set according to the application. »
According to the inactivity rate of the robot “This process corresponds to opportunistic loading. That is to say, from the moment the mobile robot has been inactive for a certain time, it is considered to be available. It will therefore take advantage of this time to recharge, even if its charge level is high. »
Depending on the constant load rate of the robot fleet : “This process can be used when the application requires the robot fleet to operate 24/7. This setting is to specify a sufficient number of robots in the fleet so that a percentage of that fleet is always charging and able to easily replace a robot that is nearing the end of its discharge cycle. »
“Mobile robots have a collective intelligence linked to the fleet manager, which manages and coordinates robots in their environment. Thanks to the fleet manager, the mobile robots will share their trajectory with all the robots present in an area with a radius of 10 m. These trajectories are considered as dynamic obstacles in order to allow robots to avoid each other and to coexist in restricted environments. »
Autonomous mobile robots are able to compensate for their own failures. Unlike a traditional industrial machine which, if it breaks down, blocks the production line. In other words, if I have a mobile robot that breaks down my deliveries will not be penalized. Indeed, it is the other mobile robots that will come to replace it.
Example: Imagine that in a fleet of 10 robots, there is a robot that breaks down. Each robot has an autonomy of 10 hours. The fleet will then become under capacity by 10%, that is to say that for 4 days the robot fleet will continue to work without stopping production. Meanwhile, the maintenance team can intervene on the breakdown of the robot.
“At Meanwhile, our main objective is to transform the complex industrial environment into an intelligent industrial environment, meeting our customers’ need for flexibility. We want to allow our customers to integrate our mobile robotic solutions in a simple and economical way, while bringing a dimension of safety, traceability and flexibility to their process. Thanks to the peri-robotic ecosystem developed by Meanwhile, our customers are able to use complex ultra-connected processes in a very intuitive way, thus facilitating their task and increasing their productivity. »
To illustrate Fabien Benoteau’s words, we can highlight the Omnibox developed by Meanwhile. The Omnibox is an electronic box that allows Meanwhile mobile robots to interface with any equipment present at the customer’s premises (elevators, racks, doors, conveyors, production machinery, etc.). Thanks to this box, the mobile robots are installed plug and play in the customer’s existing environment and interact with it natively.
Adaptable to the demand for robotic labor
Any new robot introduced into the customer installation has the ability to integrate its environment as well as all other robots. Thanks to the fleet manager, when a new robot is introduced into the environment, it takes about two minutes to join its fleet.
Autonomous mobile robots adapt very easily to agile production systems on sites of all sizes. If production cells are moved or new cells or processes are added, a new building plan can be easily and quickly transferred.
Example: My production plant is equipped with a fleet of ten robots. Five robots are responsible for delivery to the production lines and five other robots are in charge of store deliveries. Thanks to Meanwhile’s Mw² software, I will manage my production peaks by sending, automatically or manually, two robots from the store mission to assist those in charge of the “production lines” mission.
Depending on the need, autonomous mobile robots can choose how they will carry out their mission:
The First in first out (Fifo) strategy: the first mission that is created is assigned to the nearest robot and so on. In this case, the missions are carried out in order of priority.
The Non FiFo strategy: This strategy aims to optimize the distance traveled and, in fact, the energy expended by the robots.
Thanks to the resilience of Meanwhile autonomous mobile robots, companies avoid costly changes to their infrastructure and downtime when they have to rearrange the site. Companies are able to adapt to the changes imposed by the current situation by reorganizing their operational processes at lower costs, while optimizing their efficiency and competitiveness.
Interview Fabien Benoteau – Meanwhile – CTO and COO – Autonomous Mobile Robotics, a resilient system.
* CTO : Chief Technology Officer
** COO : Chief Operating Officer