The RSS Test of Time Award is given to highest impact papers published at RSS (and potentially journal versions thereof) from at least ten years ago. Impact may mean that it changed how we think about problems or about robotic design, that it brought fully new problems to the attention of the community, or that it pioneered new approach to robotic design or problem solving.
With this award, RSS generally wants to foster the discussion of the long term development of our field. The award is an opportunity to reflect on and discuss the past, which is essential to make progress in the future. The awardee’s keynote is therefore complemented with a Test of Time Panel session devoted to this important discussion.
It is our great pleasure to announce that the 2022 Test of Time Award goes to the paper:
Sertac Karaman and Emilio Frazzoli
Incremental Sampling-based Algorithms for Optimal Motion Planning
Robotics: Science and Systems VI, 2010.
Sertac Karaman and Emilio Frazzoli
Sampling-based algorithms for optimal motion planning
International Journal of Robotics Research, Vol 30 Issue 7: Special Issue on Robotics: Science and Systems 2010.
For the first formal asymptotic analysis of the quality of stochastic sampling-based path planning algorithms and the introduction of new, provably asymptotically optimal algorithms PRM and RRT, in wide use today.