mlsanityData to 14 Oct 2026

Khalasi: Energy-Efficient Navigation for Surface Vehicles in Vortical Flow Fields

arXiv 2512.06912 ↗First posted 7 Dec 2025cs.RO cs.LGcited by 0

On the map: Deep reinforcement learning methods → RL for robot navigation and UAV control

Abstract (arXiv)

For centuries, khalasi (Gujarati for sailor) have skillfully harnessed ocean currents to navigate vast waters with minimal effort. Emulating this intuition in autonomous systems remains a significant challenge, particularly for Autonomous Surface Vehicles tasked with long duration missions under strict energy budgets. In this work, we present a learning-based approach for energy-efficient surface vehicle navigation in vortical flow fields, where partial observability often undermines traditional path-planning methods. We present an end to end reinforcement learning framework based on Soft Actor Critic that learns flow-aware navigation policies using only local velocity measurements. Through extensive evaluation across diverse and dynamically rich scenarios, our method demonstrates substantial energy savings and robust generalization to previously unseen flow conditions, offering a promising path toward long term autonomy in ocean environments. The navigation paths generated by our proposed approach show an improvement in energy conservation 30 to 50 percent compared to the existing state of the art techniques.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods. Builds on 7 of its 33 references that are in the map. First posted on arXiv 7 Dec 2025.

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  1. 2025Enhancing Efficiency and Propulsion in Bio-mimetic Robotic Fish through End-to-End Deep Reinforcement Learning5 Jun

Other references · 6

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  3. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,417
  4. 2018Efficient collective swimming by harnessing vortices through deep reinforcement learningcited by 73
  5. 2021Learning Efficient Navigation in Vortical Flow Fieldscited by 26
  6. 2019Zermelo's problem: Optimal point-to-point navigation in 2D turbulent flows using Reinforcement Learningcited by 21

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  5. 2024MarineFormer: A Spatio-Temporal Attention Model for USV Navigation in Dynamic Marine Environments
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  7. 2025Goal-Conditioned Reinforcement Learning for Data-Driven Maritime Navigation
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