Energy efficiency is one of the most critical challenges in the development and deployment of autonomous drones and vehicles. Whether operating in aerial, ground, surface, or underwater environments, autonomous systems are highly constrained by limited onboard energy resources, which directly impact mission duration, computational capability, payload capacity, and operational reliability. At the same time, the increasing complexity of autonomous missions requires more advanced sensing, communication, and decision-making, further intensifying energy demands.
Artificial Intelligence (AI) offers powerful tools to address these challenges by enabling intelligent energy management, adaptive control, and optimized system-level decision-making. AI-driven approaches can significantly improve energy efficiency through intelligent path planning, dynamic resource allocation, predictive energy consumption modeling, and real-time optimization of propulsion and onboard computing systems.
This Special Issue aims to bring together cutting-edge research on AI-based energy optimization techniques for autonomous drones and vehicle systems. It focuses on developing novel algorithms, models, and frameworks that enhance energy-aware autonomy while maintaining high performance, safety, and reliability.
We welcome contributions that explore both theoretical advances and practical implementations, including simulation studies, experimental validations, and real-world deployments. The Special Issue seeks to promote interdisciplinary research bridging artificial intelligence, robotics, control engineering, and energy systems to enable the next generation of energy-efficient autonomous platforms.
The ultimate goal is to support sustainable, long-endurance, and intelligent autonomous systems capable of operating efficiently in complex and resource-constrained environments.
This Special Issue is organized in collaboration with the
Conference AIEODC 2026, aiming to extend high-quality research contributions from the conference to a broader audience.
Topics of Interest Include, but Are Not Limited To:
- AI-based energy optimization in autonomous systems
- Energy-efficient path planning and navigation
- Reinforcement learning for power management
- Predictive energy consumption modeling
- Low-power computer vision for drones
- Intelligent battery management systems
- Energy-aware swarm drone coordination
- Optimization of propulsion and control systems
- Edge AI for energy-efficient autonomy
- Multi-objective optimization in autonomous missions
- Adaptive mission planning under energy constraints
- Energy-efficient communication in UAV/UGV/USV/UUV
- Real-time energy-aware decision-making
- Sustainable autonomous system design
