Ahmad A. Almarkhi
Papers
3
Total Citations
33
H-Index
3
About
Ahmad A. Almarkhi is a robotics researcher whose work focuses on the fault tolerance and kinematic design of redundant manipulators. His core contributions lie in developing novel algorithms to analyze and optimize the self-motion manifolds of robots—the continuous sets of joint configurations that keep the end-effector stationary. Almarkhi’s 2019 paper, “Maximizing the Size of Self-Motion Manifolds to Improve Robot Fault Tolerance,” introduced a methodology for finding the largest such manifolds, directly enhancing a robot’s ability to continue operating after a joint failure. In the same year, he co-authored “Singularity Analysis for Redundant Manipulators of Arbitrary Kinematic Structure,” which presented a gradient-based technique for identifying singularities of any rank, even when singular values become nearly equal—a common challenge in complex robots. His 2020 work, “An Algorithm to Design Redundant Manipulators of Optimally Fault-Tolerant Kinematic Structure,” proposed a design algorithm targeting the theoretical maximum self-motion manifold size (n × 2π for an n-DoF robot), a benchmark rarely achieved in practice. With each paper garnering 9–12 citations, Almarkhi’s research provides foundational tools for building safer, more resilient robotic systems, making him a key voice in robot kinematics and fault-tolerant design.
Research Focus
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Top Papers
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