Papers

4

Total Citations

32

H-Index

3

About

Asanka G. Perera is a robotics researcher whose work bridges aerial robotics, human-robot interaction, and multi-agent sensing. His primary research areas include human motion analysis from UAV video, bilateral teleoperation, and multi-robot environmental mapping. Perera’s most cited work, "Human Pose and Path Estimation from Aerial Video Using Dynamic Classifier Selection" (19 citations), introduces an innovative approach to estimating human pose and trajectory from drone-mounted cameras in near real-time—a critical capability for surveillance, search-and-rescue, and autonomous navigation. He further advanced this field with "Human motion analysis from UAV video" (4 citations), which proposes a dynamic classifier selection method to address the challenges of monocular aerial imagery. In teleoperation, his review on bilateral teleoperation with force, position, power, and impedance scaling (6 citations) provides a foundational analysis of scaling techniques for dissimilar master-slave robotic systems. Most recently, Perera’s 2024 work on multi-modal, multi-robot source localization introduces a state-machine model combining exploration strategies for real-world gas mapping. With a growing citation impact and contributions spanning aerial perception, teleoperation, and collaborative robotics, Perera is establishing himself as a versatile researcher advancing practical solutions for autonomous systems in dynamic environments.

Research Focus

Key Achievements

3
H-Index
4
Papers
32
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Human Pose and Path Estimation from Aerial Video Using Dynamic Classifier Selection
19 citations · 2018
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: University of South Australia, University of Moratuwa, University of Canberra

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago