Arief Budiman
Papers
1
Total Citations
3
H-Index
1
About
Arief Budiman is a robotics researcher focused on advancing multi-robot coordination and task allocation systems. His most impactful work introduces a hybrid algorithm that combines a deterministic greedy approach with a metaheuristic genetic algorithm to optimize task distribution among specialized robot teams. This novel solution addresses the complex challenge of evenly allocating tasks while minimizing global objectives, offering significant improvements in efficiency and scalability for multi-robot systems. Though his 2024 paper has garnered 3 citations in its early stages, the work represents a foundational contribution to the field, with potential applications in warehouse automation, search-and-rescue missions, and industrial robotics. Budiman’s research bridges theoretical optimization and practical deployment, making him a promising voice in autonomous systems. His hybrid methodology stands out for its ability to balance computational simplicity with robust performance, positioning his work as a key reference for future studies in multi-agent coordination and intelligent task management.
Research Focus
Key Achievements
Top Papers
- 1