Papers
18
Total Citations
105
H-Index
7
About
Abdalla Swikir is a robotics researcher whose work spans robot motion planning, manipulation, human-robot interaction, and intelligent control systems. His research is particularly distinguished by contributions to cooperative and bimanual manipulation, where his landmark 2021 paper on reactive planning using set primitives and circular fields (21 citations) introduced a novel coupling of manipulability information with vector-field planners, enabling real-time obstacle-aware dual-arm coordination. Complementing this, his work on coordinated motion generation and object placement further advances the challenge of multi-arm task execution in cluttered environments. Swikir has also made notable strides in adaptive manufacturing, developing methods for automatic production of task-specific gripper fingertips (13 citations) to accelerate reconfigurable assembly lines. His more recent work reflects a growing engagement with cutting-edge AI, including TacDiffusion (10 citations), which applies diffusion models to high-precision tactile insertion tasks, and LLM-driven behavior tree generation (7 citations) for complex robot task planning. His teleoperation research, notably the creative "Drawing Elon Musk" robot avatar demonstration (11 citations), showcases an ability to bridge rigorous engineering with compelling real-world applications. Across more than 80 cumulative citations, Swikir's portfolio reveals a researcher consistently pushing the boundaries of safe, intelligent, and dexterous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 4Drawing Elon Musk: A Robot Avatar for Remote Manipulation11 citations · 2021
- 5TacDiffusion: Force-Domain Diffusion Policy for Precise Tactile Manipulation10 citations · 2025
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- 9Fast yet predictable braking manoeuvers for real-time robot control3 citations · 2023
- 10Optimal Control for Clutched-Elastic Robots: A Contact-Implicit Approach3 citations · 2024