Marlin Strub has had two papers on informed, sampling-based planners accepted to ICRA 2020 in Paris, France. His first is on Advanced Batch Informed Trees (ABIT*) and you can read it right now on arXiv and check out the code if you would like to try it yourself.
- Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Path planning is an active area of research essential for many applications in robotics. Popular techniques include graph-based searches and sampling-based planners. These approaches are powerful but have limitations.
This paper continues work to combine their strengths and mitigate their limitations using a unified planning paradigm. It does this by viewing the path planning problem as the two subproblems of search and approximation and using advanced graph-search techniques on a sampling-based approximation.
This perspective leads to Advanced BIT*. ABIT* combines truncated anytime graph-based searches, such as ATD*, with anytime almost-surely asymptotically optimal sampling-based planners, such as RRT*. This allows it to quickly find initial solutions and then converge towards the optimum in an anytime manner. ABIT* outperforms existing single-query, sampling-based planners on the tested problems in R4 and R8, and was demonstrated on real-world problems with NASA/JPL-Caltech.