Asma Iqbal

About

Asma Iqbal is a rising researcher in autonomous systems and artificial intelligence, with a primary focus on reinforcement learning for unmanned aerial vehicles (UAVs). Her most notable contribution is the development of a multi-goal reinforcement learning framework for motion planning of quadrotor UAVs in three-dimensional cluttered environments. This work addresses a critical challenge in robotics: enabling drones to navigate toward unseen, randomly placed goals without prior knowledge of the environment. By integrating goal-conditioned policies with robust obstacle avoidance, Iqbal’s framework enhances the adaptability and safety of autonomous flight. Although her citation count is currently modest—with her leading paper garnering 1 citation—the novelty of her approach positions her as an emerging voice in the field. Her research bridges the gap between theoretical reinforcement learning and practical drone deployment, offering solutions for applications in search-and-rescue, surveillance, and delivery systems. As her work gains recognition, Iqbal is poised to make significant strides in intelligent motion planning and autonomous navigation.

Research Focus

Key Achievements

Top Papers

1. 1
   A multi-goal reinforcement learning framework for motion planning of a quadrotor UAV in 3D cluttered environment with unseen random goals

   1 citations · 2025

Key Collaborators

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