Topological Belief Space Planning

In this research project we introduce a novel concept, topological belief space planning (BSP), that uses topological properties of the underlying factor graph representation of future posterior beliefs to direct the search for an optimal solution. This concept deviates from state-of-the-art BSP approaches and is motivated by recent results which indicated, in the context of graph pruning, that topological properties of factor graphs dominantly determine the estimation accuracy. Topological space is also often less dimensional than the embedded state space. In particular, we show how this novel concept can be used in multi-robot decentralized belief space planning in high-dimensional state spaces to overcome drawbacks of state-of-the-art approaches: computational intractability of an exhaustive objective evaluation for all candidate path combinations from different robots and dependence on the initial guess in the announced path approach, which can lead to a local minimum of the objective function.

Related Publications:

Journal Articles

  1. A. Kitanov and V. Indelman, “Topological Belief Space Planning for Active SLAM with Pairwise Gaussian Potentials and Performance Guarantees,” International Journal of Robotics Research (IJRR), no. 1, 2024.
    Kitanov24ijrr.pdf DOI: 10.1177/02783649231204898
  2. M. Shienman, A. Kitanov, and V. Indelman, “FT-BSP: Focused Topological Belief Space Planning,” IEEE Robotics and Automation Letters (RA-L), no. 3, Jul. 2021.
    Shienman21ral.pdf Shienman21ral.slides DOI: 10.1109/LRA.2021.3068947

Technical Reports

  1. A. Kitanov and V. Indelman, “Topological Information-Theoretic Belief Space Planning with Optimality Guarantees,” 2019.

Conference Articles

  1. A. Kitanov and V. Indelman, “Focus on What Matters: Topological Aspects in Information-Theoretic Belief Space Planning,” in Workshop on Topological Methods in Robot Planning, in conjunction with the IEEE International Conference on Robotics and Automation (ICRA), May 2019.
    Kitanov19icra_ws.pdf Kitanov19icra_ws.slides Kitanov19icra_ws.poster
  2. A. Kitanov and V. Indelman, “Topological Multi-Robot Belief Space Planning in Unknown Environments,” in IEEE International Conference on Robotics and Automation (ICRA), May 2018.
    Kitanov18icra.pdf Kitanov18icra.poster