Marlin has been working on planning problems that seek to optimize the distance between paths and obstacles. This is a difficult problem for informed search algorithms, like A*, because there aren't very many effective and cost-efficient admissible heuristics for obstacle clearance. He's written up a short technical note on an admissible heuristic for clearance in search space that you can find on arXiv.
Welcome to the Estimation, Search, and Planning (ESP) research group, a member of the Oxford Robotics Institute (ORI). We motivate a knowledge-based approach to robotics research by taking on challenging, real-world problems. We do this to test our solutions and force us to understand the fundamental challenges of next-generation robots.
Please have a look around our website to find out more about who we are and what we do, including our publicly available code and datasets. You may also be interested in our Twitter, YouTube, and GitHub accounts.
Marlin's paper at IROS 2020 with the NASA JPL Robotic Surface Mobility Group on tethered-rover autonomy was a finalist for the Best Paper Award on Safety, Security, and Rescue Robotics. You can check out this great article on the mission concept or download an open-access copy of the paper to learn more. Well done everyone!
Another ESP paper at virtual IROS is Rowan's latest work on NBV planning for autonomous 3D reconstruction. It presents an updated Surface Edge Explorer (SEE++) algorithm that considers more information and is available as open source code. If you'd like to know more, there's a trailer video and presentation on YouTube and you can read the paper on arXiv.