mlsanityData to 14 Oct 2026

Reinforcement Learning-Based Energy-Aware Coverage Path Planning for Precision Agriculture

arXiv 2601.16405 ↗First posted 23 Jan 2026cs.RO cs.LGcited by 6

On the map: Deep reinforcement learning methods → RL for energy, networks and operations

Abstract (arXiv)

Coverage Path Planning (CPP) is a fundamental capability for agricultural robots; however, existing solutions often overlook energy constraints, resulting in incomplete operations in large-scale or resource-limited environments. This paper proposes an energy-aware CPP framework grounded in Soft Actor-Critic (SAC) reinforcement learning, designed for grid-based environments with obstacles and charging stations. To enable robust and adaptive decision-making under energy limitations, the framework integrates Convolutional Neural Networks (CNNs) for spatial feature extraction and Long Short-Term Memory (LSTM) networks for temporal dynamics. A dedicated reward function is designed to jointly optimize coverage efficiency, energy consumption, and return-to-base constraints. Experimental results demonstrate that the proposed approach consistently achieves over 90% coverage while ensuring energy safety, outperforming traditional heuristic algorithms such as Rapidly-exploring Random Tree (RRT), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) baselines by 13.4-19.5% in coverage and reducing constraint violations by 59.9-88.3%. These findings validate the proposed SAC-based framework as an effective and scalable solution for energy-constrained CPP in agricultural robotics.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Placed in RL for energy, networks and operations, one of 15 directions in Deep reinforcement learning methods. Builds on 8 of its 36 references that are in the map. First posted on arXiv 23 Jan 2026.

Builds on

8 of 36 references.

References · 8

  1. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  2. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,417
  3. 2024Prioritized Information Bottleneck Theoretic Framework with Distributed Online Learning for Edge Video Analyticscited by 17
  4. 2025Enhancing Vehicular Platooning with Wireless Federated Learning: A Resource-Aware Control Frameworkcited by 9
  5. 2025Shared Spatial Memory Through Predictive Codingcited by 7
  6. 2022Fields2Cover: An open-source coverage path planning library for unmanned agricultural vehiclescited by 5
  7. 2024Energy-aware Multi-UAV Coverage Mission Planning with Optimal Speed of Flightcited by 3
  8. 2025Task-Oriented Semantic Compression for Localization at the Network Edgecited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memorycited by 9
  2. 2026Lifecycle-Aware Federated Continual Learning in Mobile Autonomous Systemscited by 7
  3. 2026CrystalMem: Elastic Memory for Self-Evolving LLM Agents via Knowledge Crystallizationcited by 2
  4. 2026ERRAND: Budgeted Maintenance of Agent Memorycited by 1
  5. 2026When Unlearning Fails: Reliable Data Deletion under Post-Training in Agent Networkscited by 0
  6. 2026Not All Experience Belongs in the Weights: Component Routing for Self-Improving GUI Agentscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning
  2. 2025Optimizing Navigation And Chemical Application in Precision Agriculture With Deep Reinforcement Learning And Conditional Action Tree
  3. 2024Sim-to-Real Transfer of Deep Reinforcement Learning Agents for Online Coverage Path Planning
  4. 2025Sustainable Smart Farm Networks: Enhancing Resilience and Efficiency with Decision Theory-Guided Deep Reinforcement Learning
  5. 2024A Deep Reinforcement Learning Approach to Battery Management in Dairy Farming via Proximal Policy Optimization
  6. 2025JPDS-NN: Reinforcement Learning-Based Dynamic Task Allocation for Agricultural Vehicle Routing Optimization
  7. 2026Forecast Aware Deep Reinforcement Learning for Efficient Electricity Load Scheduling in Dairy Farms
  8. 2024A Reinforcement Learning Approach to Dairy Farm Battery Management using Q Learning