Vecna?s robotic logistics solutions are a family of autonomous mobile robots, built to operate within human-centric environments. These hard-working robots are capable of handling up to 4500 kg while rapidly and safely responding to dynamic environments. In addition, these free agents are team players ? they coordinate on their own and report problems as soon as they arise.
The navigation system the robots use makes robust and reliable, allowing them to continue to make progress toward their high-level mission goals in dynamic and unstructured environments. Our system also includes continuous execution monitoring to track progress in real-time, and to detect and anticipate potential problems as early as possible. This capability enables our robots to communicate meaningful status information to users (e.g., anticipated time of arrival, schedule deviations, etc.), and to dynamically and proactively respond to any run-time disturbances.
Our solution offers a quick deployment process with little to no infrastructure changes, and simple reconfigurability when facilities or needs change. Customers are able to use our robots in dynamic environments and around people, two areas that cause significant problems for the previous generation of robotic platforms. The robot thinks about the world in terms of which hallways and elevators to take. Machine learning is used to intelligently avoid trouble spots, like the cafeteria during the lunch-time rush.
Of course, the robot can also be precise when needed–its motion planners allow it to nimbly dodge people and obstacles in crowded, dynamic spaces.
Our navigation system is applicable in many applications, including hospitals and manufacturing/warehousing facilities. In hospitals, nurses walk upwards of 5 miles per shift, spending a considerable portion of their time pushing carts and waiting for elevators. Our approach allows nurses to focus on value-add functions such as patient care, while simultaneously increasing the reliability and consistency of deliveries.
In manufacturing/warehousing facilities, our system can act like a virtual conveyor belt. Physical conveyor belts can cost $1000/meter to install, and can not be reconfigured without major construction efforts, whereas the robot can be reconfigured with a simple software update.
We developed our navigation system to be generally applicable to robots of all shapes, sizes, and drive configurations. We also developed our system to be generally applicable to a wide variety of environments, not just focusing on wall-following or line-following. Avoiding these commonly applied shortcuts resulted in a very powerful and extensible navigation system that now powers our full line of robotic platforms. This approach enables the widespread adoption of mobile robots in peopled spaces, opening up billions or even trillions of market needs to increased automation.
