Introducing the International Journal of Robotics Paper of the Year Award

Last week the inaugural International Journal of Robotics (IJRR) Research Paper of the Year award was presented at the Robotics: Science and Systems conference.  The award seeks to recognize research that has the most potential impact within the field of Robotics and support its engagement within the wider field of academia.

The inaugural winners of the award were Anirudha Majumdar and Russ Tedrake for their paper Funnel libraries for real-time robust feedback motion planning. Speaking about their research and its potential impact, Majumdar and Tedrake remarked:

Imagine an unmanned aerial vehicle (UAV) navigating aggressively through a cluttered urban environment in order to deliver a package in time, a legged robot swiftly traversing rough terrain in a disaster-stricken region, or an autonomous car manoeuvring through heavy traffic. The incredible pace at which such machines are being adopted by a burgeoning robotics industry poses fundamental theoretical and practical challenges. These applications demand that the robot move through (and in certain cases interact with) its environment with extreme agility while still being in very close proximity to humans. Such systems today lack guarantees on their safety and can fail dramatically in the face of uncertainty in their environment and dynamics.

Our paper seeks to address some of these challenges by developing algorithmic approaches for controlling robotic systems in a manner that allows us to make guarantees on their safety. In particular, the ability to plan and execute motions in a safe and reliable manner is critical to the operation of most robotic systems. This is particularly challenging for systems such as UAVs whose dynamics are highly nonlinear and are subject to external disturbances (e.g., wind gusts). Further, these systems must be able to react in real-time to unexpected obstacles while navigating at high speeds. In order to tackle these challenges, we leverage computational tools from convex optimization and nonlinear control to develop verifiably safe algorithms for control and real-time planning for robotic systems.

We believe that the ability to provide such guarantees on safety will be crucial to our ability to reliably and confidently deploy robotic systems that operate in the real world.

Congratulations to Anirudha Majumdar and Russ Tedrake on winning the award. We look forward to seeing its impact on the field and to seeing what new and exciting research the award uncovers next year!

If you are interested in reading the full paper, you can access it here.

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