Scientific Challenges

RoboCup@Work addresses many of the standard scientific challenges for robotics, including the following non-exhaustive list:

  • Perception in static and dynamic environments under varying environmental conditions
  • Path planning and motion control of mobile bases in dynamic environments
  • Grasp planning, trajectory planning, and motion control of mobile manipulators
  • Planning and decision making
  • Representation of plans, knowledge, strategy and tactics
  • Adaptivity and learning
  • Cooperation in both cooperative and competitive environments
  • Human-robot and robot-robot interaction
  • Design, construction, and operation of robust robots at affordable cost
  • Simulation, evaluation, and benchmarking of advanced robot systems

In addition, the RoboCup@Work League specifically targets several new challenges, which so far are not pursued by other competitions or RoboCup leagues:

  • Mobile Manipulation: While until the recent past industrial robotics concentrated on highly-precise but non-mobile manipulators, mobile robots either had no manipulators or only low-DoF robot arms. Recently, this situation is changing, and both the research community as well as industry have developed a strong interest in serious and robust mobile manipulators. Introducing a competition that fosters research in that direction comes very timely.
  • Logistics: Logistics is an enormously important area in practically every business-related domain. It plays practically no role in any of the established RoboCup leagues so far. Rescue simulation league is a notable exception, but poses quite different constraints on logistics problems than those targeted by RoboCup@Work.
  • Cooperative Mobile Manipulation: Once mobile manipulators are not a fantasy any more but reality, the next step would be to have such mobile manipulators cooperate with humans and/or other mobile manipulators. Reaching this objective requires solving numerous additional problems, but also opens many new application scenarios.
  • Multiagent Planning and Scheduling, and Multi-Criteria Optimization: The value of classical task planning in soccer and rescue leagues is rather limited; if it used at all, these planners have to deal with constraints that are quite different from those in most industrial domains. Task planning may eventually be of great interest in RoboCup@Home, but so far most teams work with preprogrammed scripts or state machines executing routine activities. In RoboCup@Work, however, multiagent planning and scheduling with multi-criteria optimization is of immediate interest, and has a large potential for innovative applications.