RoboCup Industrial

@Work League

RoboCup@Work is a segment of RoboCup within the RoboCup Industrial domain, focusing on the integration and advancement of robotics in work-related scenarios. This competition is pivotal in stimulating research and development in the field, particularly in the creation and enhancement of autonomous mobile robots. The core objective is to facilitate and enhance robotic assistance in diverse areas such as manufacturing, automation, parts handling, artificial intelligence, and the broader aspects of logistics. 

Central to RoboCup@Work's ethos is the collaboration between robots and human workers, aiming to tackle complex tasks more efficiently. This collaboration is showcased in an international arena, where teams from across the globe bring their robotic innovations to compete. The competition encompasses a variety of challenging tasks that each robot must adeptly perform. These tasks include autonomous navigation, object recognition, and the manipulation of objects. Through this competitive yet collaborative environment, RoboCup@Work propels the boundaries of robotic capabilities. 

More information:
@Work site
LOC: Stefan Clercx ✉

Logistics League

ARM Challenge

The RoboCup Autonomous Robot Manipulation (ARM) challenge is an affiliated educational event in which participants learn to program a robotic arm to sort objects on a table. Participants learn object recognition for color and shape, and implement controls to pick up and sort these objects. The best teams from the online simulation qualifier are invited to attend RoboCup in person to test their software on a real robotic arm. 

Educational and training material, webinars, on-line meetings, and off-line resources are provided by MathWorks and RCF so students previously unfamiliar with RoboCup can get involved in the competition and transition to leagues such as @Home or @Work where challenges also include identifying objects (albeit household objects, or items in an industrial setting), and properly interacting with these objects in the robot’s environment.

More information:
ARM site
LOC: Jorrit Olthuis ✉