Optimizing Energy Efficiency in Multi-Robot Systems through Adaptive Control and AI-Driven Motion Planning
Year: 2025
Type: preprint
Abstract: In the pursuit of sustainable and energy-efficient robotic systems, this research investigates the optimization of energy consumption in multi-robot systems through the integration of adaptive control strategies and AI-driven motion planning. The primary objective is to develop a comprehensive framework that minimizes energy usage while maintaining high performance and reliability in collaborative robotic tasks. By leveraging artificial intelligence, the study introduces advanced algorithms for dynamic path planning and real-time scheduling, enabling robots to adapt their behavior based on environmental feedback and changing task requirements. The research involves the design and implementation of energy-aware motion planning techniques that reduce unnecessary movements and optimize trajectories. Additionally, it focuses on the development of energy-efficient hardware components, including actuators and power management systems, to further enhance overall system efficiency. Human-robot interaction is also explored to determine how cooperative behaviors can contribute to energy savings. Empirical evaluations are conducted through a series of case studies in industrial automation, agricultural robotics, and mobile robot applications. These case studies demonstrate the practical applicability and effectiveness of the proposed methods in real-world scenarios. The results indicate significant improvements in energy efficiency, with multi-robot systems achieving tasks with reduced energy consumption without compromising on performance.The conclusions highlight the potential of combining adaptive control and AI-driven motion planning in creating sustainable robotic systems. The findings provide valuable insights into best practices for energy optimization in robotics, paving the way for future research and development in this critical area. This research contributes to the growing field of sustainable robotics, offering solutions that align with global efforts to reduce energy consumption and promote environmental sustainability.
Authors: ABHIJIT TRIPATHY, Isha Pandey
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414365030
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