Papers
2
Total Citations
5
H-Index
2
About
Freddy Liendo is a rising researcher at the forefront of human-robot collaboration (HRC), with a focused expertise in motion planning, learning from demonstration, and robot-agnostic control systems. His work is distinguished by the innovative application of dual quaternion mathematics to enhance Dynamic Movement Primitives (DMPs), a core method for teaching robots complex, stable behaviors. Liendo’s major contributions address two critical challenges in robotics: enabling safe obstacle avoidance in collaborative systems and achieving versatile, task-agnostic skill transfer. His 2023 paper on an improved dual quaternion DMP formulation for obstacle avoidance in HRC as a System of Systems (SoS) has garnered early attention (3 citations), laying a foundation for safer human-robot interaction. Building on this, his 2025 work introduces a robot-agnostic algorithm for learning and executing throwing tasks, demonstrating how DMPs can generalize across different robotic platforms (2 citations). Though early in his career, Liendo’s integration of dual quaternion theory with DMPs represents a significant step toward more adaptive, intuitive, and safe robotic systems—a promising trajectory for the future of collaborative robotics.
Research Focus
Key Achievements
Top Papers
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