Asif Rizwan

KTH Royal Institute of Technology, National University of Sciences and Technology

Papers

Total Citations

H-Index

About

Asif Rizwan’s research focuses on advancing robotic manipulation and motion planning, with a particular emphasis on dexterous in-hand manipulation and whole-body control for humanoid robots. His most cited work, "Placing Objects with prior In-Hand Manipulation using Dexterous Manipulation Graphs" (2019, 7 citations), introduces a novel approach that enables robots to adjust a grasped object’s pose using in-hand manipulation before placing it to maximize a placement preference function—a critical capability for tasks requiring precision and adaptability. Rizwan also tackles the high-dimensional challenge of humanoid locomotion and stability in "Whole-body motion planning for humanoid robots with heuristic search" (2016, 3 citations) and its extension, "Whole-body motion and footstep planning for humanoid robots with multi-heuristic search" (2019, 2 citations). These works integrate footstep and whole-body motion planning with multi-heuristic search algorithms, addressing the complex constraints of obstacle avoidance and efficient movement in high-DOF systems. While his citation counts reflect an early-career trajectory, Rizwan’s contributions are notable for bridging dexterous manipulation and whole-body planning—two traditionally separate domains—offering practical pathways for robots to perform intricate, real-world tasks. His work is particularly relevant for researchers in autonomous robotics and human-robot interaction.