About

Adrian Arellano-Delgado is a robotics and control systems researcher whose work spans mobile robot trajectory tracking, chaotic systems, and swarm robotics. His research has made meaningful contributions to the control of differential-drive wheeled mobile robots, developing novel algorithms that solve complex tracking problems using minimal sensor information — a notable example being his 2021 paper on trajectory tracking using only Cartesian position measurements, which has garnered 44 citations and represents a significant step toward practical, low-cost robot navigation. A distinctive thread in his research is the intersection of chaos theory and robotics. His 2022 work on generating chaotic trajectories using the Hénon map (21 citations) and his 2019 analysis of chaotic system degradation in embedded implementations (13 citations) demonstrate a unique expertise in applying nonlinear dynamics to autonomous systems, with implications for cryptography and coverage tasks. Arellano-Delgado has also advanced swarm robotics, proposing control algorithms that produce emergent self-organized behaviors — including aggregation and flocking — in multi-robot systems. With growing citation counts across a focused and coherent body of work, he is an emerging voice in autonomous mobile robotics and nonlinear control theory.

Research Focus

Key Achievements

5
H-Index
6
Papers
102
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Trajectory tracking of wheeled mobile robots using only Cartesian position measurements
44 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Consejo Nacional de Humanidades, Ciencias y Tecnologías, Universidad Autónoma de Baja California, Consejo Nacional de Ciencia y Tecnología

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago