Papers
3
Total Citations
49
H-Index
2
About
Anoush Sepehri is a robotics researcher whose work spans motion planning for rigid manipulators and the emerging frontier of soft robotic systems. His most cited paper, “A Motion Planning Algorithm for Redundant Manipulators Using Rapidly Exploring Randomized Trees and Artificial Potential Fields” (2021, 41 citations), introduces a hybrid navigation strategy that fuses two classic approaches—RRTs and artificial potential fields—to efficiently solve complex path-planning problems for high-degree-of-freedom robots. This contribution has provided a practical framework for improving the speed and reliability of manipulator motion in cluttered environments. More recently, Sepehri has turned his attention to wearable and mesoscale soft robotics. In “A Soft Robotic Wrist Orthosis Using Textile Pneumatic Actuators For Passive Rehabilitation” (2024, 7 citations), he addresses critical challenges in developing accessible, on-body actuation for rehabilitation, emphasizing safety and compliance. His 2025 work, “Bundled Liquid Crystal Elastomer Actuators With Integrated Cooling for Mesoscale Soft Robots” (1 citation), tackles the fundamental trade-off between force output and response speed in thermally-driven LCE actuators, proposing an integrated cooling solution to enhance performance. Sepehri’s research is notable for bridging classical robotics algorithms with next-generation soft materials, offering practical pathways toward safer, more capable robotic systems for real-world applications.
Research Focus
Key Achievements
Top Papers
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