Control
Full MPC Navigation Stack
ROS 2 navigation using CasADi, IPOPT, Python, and NUMBA acceleration for optimal path generation and tracking.
Open to research collaborations
Robots that perceive, reason, and act.
Nitesh Subedi is a Ph.D. researcher at Iowa State University advancing autonomous navigation, robot learning, and vision-language systems.
Selected work
2
Publications
10+
Projects
86.7%
Sim2Real Success
4×
Robocon Campaigns
Research focus
From mechanical systems to embodied intelligence.
I am a Ph.D. researcher in Mechanical Engineering at Iowa State University and a Graduate Research Assistant. My work spans reinforcement learning for robotic manipulation, robot navigation using LLMs and VLMs, and model predictive control.
Before starting my Ph.D., I worked as an R&D Engineer at NSDeVil on autonomous navigation for wheeled robots. My engineering background connects mechanical design, controls, perception, and learning.
Robot learning
Autonomous navigation
Vision-language models
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Vision-language navigation · arXiv
LCLA: Language-Conditioned Latent Alignment
Aligns sensory observations to a latent representation of an expert policy. A lightweight adapter decouples perception from control, enabling expert behavior reuse across sensing modalities.
Robot learning · ICRA 2026
Find the Fruit
A zero-shot sim2real reinforcement learning framework for occlusion-aware plant manipulation. By separating kinematic planning from compliant control, the system achieves an 86.7% success rate in exposing target fruits.
Engineering breadth
Research grounded in complete robotic systems.
Work moves from dynamics and control through perception and learning, with deployment as the final test.
Perception
Computer Vision
Object detection, tracking, person re-identification, and visual perception using PyTorch, YOLO, DeepSort, and OpenCV.
Hardware
Mechanical Systems
Robot design, fabrication, embedded systems, controls, and four ABU Robocon campaigns.
Building intelligent systems for difficult environments.
Interested in research collaborations across robotics, autonomous navigation, manipulation, and embodied AI.