Many automation tasks are amenable to being performed by multiple robots working together within the same work-cell. The robots can perform similar jobs—for example, painting different portions of an object—or they can perform different jobs, like wrapping and packaging. In the case of heterogenous jobs, you might even want to use different robots that are tailored for each job. Regardless of the task, the goal of multi-robot cells is speed; more robots working together can finish a job sooner than a single robot.
The key challenge in deploying multi-robot work-cells is deconfliction: ensuring that the robots avoid collisions with each other. Imagine a kitchen with one chef preparing a meal—they can move wherever they please. However, if we add more chefs, then the chefs have to be careful to not bump into each other. Now imagine writing software that controls robotic chefs with the goal of optimizing performance: minimizing the time to prepare food and guaranteeing that the chefs never collide.
Typically, to control robots in a multi-robot work-cell, expert robotics software engineers spend a very long time writing software that ensures collisions are avoided. The demand for collision avoidance coupled with the expense of software engineering often leads to suboptimal solutions that do not take full advantage of robots such as exaggerated movements to give plenty of buffer room or only allowing a single robot to move at a time. Worse, if any of the jobs or any of the robots change in any way, then the software engineer must recheck every robot motion and interlock to ensure they are still collision-free. Thus, despite the appeal of multi-robot work-cells, previous solutions for implementing them have been expensive and fragile.
At Realtime Robotics, we have solved this important problem with our ground-breaking technology that solves deconfliction bottlenecks. Our solution enables each robot to account for the motion plans of all other robots in real-time while simultaneously providing each robot with its own collision-free motion plan. The primary burdens of multi-robot work-cells, discovering motion plans for the robots that do not collide and validating the motion plans during deployment, are simplified by our technology. Our solution can be deployed with any robot and adapts to on-the-fly changes in the task and changes in the robots and even robot failures. This saves robotics software engineers from having to constantly re-validate software during deployment, thus reducing the overall time and cost of multi-robot workcell deployment.
Our next post will explore in more detail how we have reconfigured deconfliction!
