mlsanityData to 14 Oct 2026

Sequential Bayesian Optimization for Adaptive Informative Path Planning with Multimodal Sensing

arXiv 2209.07660 ↗First posted 16 Sep 2022cs.AI cs.ROcited by 4

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Abstract (arXiv)

Adaptive Informative Path Planning with Multimodal Sensing (AIPPMS) considers the problem of an agent equipped with multiple sensors, each with different sensing accuracy and energy costs. The agent's goal is to explore the environment and gather information subject to its resource constraints in unknown, partially observable environments. Previous work has focused on the less general Adaptive Informative Path Planning (AIPP) problem, which considers only the effect of the agent's movement on received observations. The AIPPMS problem adds additional complexity by requiring that the agent reasons jointly about the effects of sensing and movement while balancing resource constraints with information objectives. We formulate the AIPPMS problem as a belief Markov decision process with Gaussian process beliefs and solve it using a sequential Bayesian optimization approach with online planning. Our approach consistently outperforms previous AIPPMS solutions by more than doubling the average reward received in almost every experiment while also reducing the root-mean-square error in the environment belief by 50%. We completely open-source our implementation to aid in further development and comparison.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 10 of its 35 references that are in the map. First posted on arXiv 16 Sep 2022.

Builds on

10 of 35 references.

References · 10

  1. 2017Online algorithms for POMDPs with continuous state, action, and observation spacescited by 84
  2. 2019Scalable Exact Inference in Multi-Output Gaussian Processescited by 25
  3. 2018An informative path planning framework for UAV-based terrain monitoringcited by 24
  4. 2021Adaptive Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensingcited by 14
  5. 2020Adaptive Informative Path Planning with Multimodal Sensingcited by 9
  6. 2017Sequential Bayesian Optimisation as a POMDP for Environment Monitoring with UAVscited by 7
  7. 2014Efficient Planning under Uncertainty with Macro-actionscited by 4
  8. 2015Modeling Curiosity in a Mobile Robot for Long-Term Autonomous Exploration and Monitoringcited by 2
  9. 2022Informative Path Planning to Estimate Quantiles for Environmental Analysiscited by 1
  10. 2022Risk-aware Meta-level Decision Making for Exploration Under Uncertaintycited by 1

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Cited by year

Citing papers per year: 2023: 1; 2024: 3.

4 papers.

  1. 2024Deep Reinforcement Learning with Dynamic Graphs for Adaptive Informative Path Planningcited by 7
  2. 2023Semi-Supervised Active Learning for Semantic Segmentation in Unknown Environments Using Informative Path Planningcited by 6
  3. 2024Scalable Multi-Robot Informative Path Planning for Target Mapping via Deep Reinforcement Learningcited by 1
  4. 2024MEXGEN: An Effective and Efficient Information Gain Approximation for Information Gathering Path Planningcited by 0