Agus Buono
Papers
7
Total Citations
36
H-Index
4
About
Agus Buono is a robotics researcher specializing in autonomous navigation, multi-robot coordination, and bio-inspired control systems for mobile robots. His work focuses on developing efficient algorithms for leg coordination in hexapod robots, where he proposed a tripod-gait movement algorithm using inverse kinematics to simplify leg coordination (12 citations). Buono has made significant contributions to wheeled robot control, designing a backpropagation neural network-based direct inverse controller for autonomous navigation (9 citations) and a task-oriented robot for search and rescue missions (4 citations). His recent research advances reinforcement learning for path planning, introducing a modified Q-Learning algorithm with reduced states for real-time mobile robot navigation (4 citations) and a motivation model for multi-robot path planning (3 citations). Buono also applies swarm intelligence to agricultural robotics, modifying the Ant Colony Optimization algorithm for multi-agent task allocation among UAVs (2 citations). His work on smart parallel parking for collaborative robots (2 citations) demonstrates practical applications in cooperative robotics. With over 36 citations across his publications, Buono’s research bridges theoretical algorithm development and real-world robotic applications, particularly in agriculture and search-and-rescue operations.
Research Focus
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Top Papers
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