Amir Hoshang Bakhtiary

Papers

Total Citations

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About

Amir Hoshang Bakhtiary is a researcher whose work lies at the intersection of robotic manipulation and motion planning, with a particular focus on dexterous grasping and object interaction. His most cited contribution, a 2009 paper on probabilistic roadmap (PRM) algorithms for wheeled-tip robots, introduces an efficient method for incorporating force closure (FC) verification directly into the planning process—eliminating the need for intermediate FC checks and significantly streamlining the generation of stable, manipulation-ready paths. This work, which has gathered 4 citations, demonstrates his ability to bridge theoretical rigor with practical algorithmic efficiency. Beyond this, Bakhtiary’s research addresses the broader challenge of enabling robots to manipulate polygonal objects with precision, leveraging geometric reasoning and probabilistic sampling to ensure both motion feasibility and grasp stability. His contributions are particularly valuable for advancing autonomous systems in manufacturing and service robotics, where reliable, force-aware planning is critical. For students and researchers, Bakhtiary’s work offers a clear example of how classic planning frameworks can be adapted to meet the nuanced demands of physical interaction, making it a concise but impactful reference in the field of robotic manipulation.