Prakash, Surya and Sharma, Bibhya N. (2025) Pathfinding in Autonomous Robotics: Balancing Risk, Energy, and Environmental Impact in Diverse Path Networks. In: Artificial Intelligence: Theory and Applications. Lecture Notes in Networks and Systems, 5588 . Springer Nature, Singapore. ISBN 978-981-96-1917-7
Full text not available from this repository.Abstract
It is essential that robots are able to navigate efficiently and safely within complex, unknown environments. This paper presents a novel path-planning framework that minimizes risk, energy consumption, and environmental impact through multi-objective optimization. The number of potential paths that it can evaluate for any given set of environmental conditions is obtained using advanced Monte Carlo simulations, which take into account factors such as energy efficiency, navigation safety, and environmental impact. Integrating an Environmental Impact Score (EIS) allows for addressing pathfinding in a more holistic way that covers the trail of the robotic operation. Providing comprehensive data about each possible outcome, three-objective optimization selects paths that offer optimal trade-offs between the three objectives. This ensures that users can make the most optimum, informed decisions by their specific operational strategies and environmental goals. Experimental validation via detailed simulations shows the increasing operational range, safety, and nature sustainability for autonomous robots. It is essential to demonstrate adaptable user-centric decision support to manage the complexities of accurate world navigation to enhance the dependability of autonomous robots with under operational control. The overall balance of these conflicting objectives in the framework makes sure that, under such a safe architecture, more challenging areas for robots’ navigation entail less risk and energy consumption while at the same time minimizing the environmental track. This robustness of the Monte Carlo simulations can assure the reliability of the framework and allow its adaptation to different unforeseen situations and environmental conditions. This new approach will further the domain of robotic navigation and instill that environmental considerations be part and parcel of technological development. Through the development of an interplay between operational efficiency and ecological responsibility, the proposed pathfinding framework makes a stride toward systems that are autonomous and, at the same time, high-performing and sustainable.
| Item Type: | Book Chapter |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | School of Information Technology, Engineering, Mathematics and Physics (STEMP) |
| Depositing User: | Ms Shalni Sanjana |
| Date Deposited: | 30 Jun 2025 03:25 |
| Last Modified: | 30 Jun 2025 03:25 |
| URI: | https://repository.usp.ac.fj/id/eprint/15059 |
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