Malaika Zafar
Papers
1
Total Citations
2
H-Index
1
About
Malaika Zafar is a rising researcher at the forefront of intelligent robotics and autonomous systems, with a core focus on heterogeneous multi-robot coordination and vision-language navigation. Her most cited work, “SwarmVLM: VLM-Guided Impedance Control for Autonomous Navigation of Heterogeneous Robots in Dynamic Warehousing” (2025, 2 citations), introduces a pioneering framework that integrates Vision-Language Models (VLMs) with impedance control to enable seamless collaboration between UAVs and AGVs in complex logistics environments. By addressing the complementary limitations of aerial and ground robots—such as UAV battery constraints and AGV terrain restrictions—Zafar’s research advances real-time, adaptive swarm behavior for dynamic warehousing. Though early in her career, her contributions are notable for bridging high-level semantic reasoning with low-level physical control, a critical step toward fully autonomous industrial ecosystems. Her work has already garnered attention for its practical implications in smart manufacturing and logistics, positioning her as an emerging voice in embodied AI and multi-agent systems. Zafar’s innovative approach promises to reshape how heterogeneous robot teams perceive, plan, and act in unstructured, human-centric spaces.
Research Focus
Key Achievements
Top Papers
- 1