Expected Free Energy-based Informative Path Planning for Robotic Mars Exploration

Expected Free Energy-based Informative Path Planning for Robotic Mars Exploration

|Authors: Ajith Anil Meera, Pablo Lanillos, Wouter Kouw

|Venue: arXiv preprint | Year: 2026

|arXiv: 2608.14466v1

Abstract

An autonomous robot efficiently exploring an unknown environment, such as looking for water sources on Mars, faces two simultaneous demands: building an accurate information map while quickly finding the regions of greatest value, and paying for every meter of travel and the cost of every measurement it takes. Classical information-seeking and reward-seeking criteria address only one of these objectives at a time. Here, we propose Expected Free Energy (EFE), the principled action-selection objective from active inference, as a unifying criterion for budgeted robotic informative path planning. Maintaining a Gaussian-process belief over the information field, our agent plans continuous trajectories that minimize expected free energy under hard path-length constraints. The results from multiple realizations show that EFE-based planning yields accurate posterior maps and locates the highest-value regions simultaneously, outperforming information-theoretic baselines under the same settings. In robotic exploration, these unified, easy-to-tune principled information-gathering strategies facilitate autonomous deployment while enforcing efficiency and resource constraints.

Key Contributions

• An autonomous robot efficiently exploring an unknown environment, such as looking for water sourc…
• Classical information-seeking and reward-seeking criteria address only one of these objectives at…
• Here, we propose Expected Free Energy (EFE), the principled action-selection objective from activ…
• Maintaining a Gaussian-process belief over the information field, our agent plans continuous traj…
• The results from multiple realizations show that EFE-based planning yields accurate posterior map…

Topics

• planning

Code & Data

No code repository linked in paper metadata.

BibTeX

@article{Meera2026_260814466v1,
  title     = {Expected Free Energy-based Informative Path Planning for Robotic Mars Exploration},
  author    = {Ajith Anil Meera and Pablo Lanillos and Wouter Kouw},
  year      = {2026},
  eprint    = {2608.14466v1},
  archivePrefix = {arXiv},
  primaryClass  = {cs.RO},
  url       = {https://arxiv.org/abs/2608.14466v1}
}