Senthil Hariharan Arul

Motion Planning Lead at AlphaZ
Robotics | Motion Planning | Planning under Uncertainty | Reinforcement Learning

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Email: sarul1@umd.edu

Curriculum Vitae

I am currently the Motion Planning Lead at AlphaZ. I recently defended my Ph.D. in Electrical and Computer Engineering at the University of Maryland, College Park, where I was advised by Prof. Dinesh Manocha. My research integrates robotics, motion planning, and reinforcement learning to advance AI technology, with a focus on multi-robot coordination, navigation, and social navigation. Specifically, I specialize in cooperative navigation and motion planning under uncertainty, exploring innovative solutions for real-world applications. In addition, I completed two internships at Amazon Lab126, specifically with the Consumer Robotics group. Currently, I am interning with Honda Research Institute (HRI) for Spring 2025, where I am working on interactive motion planning and decision-making in the context of autonomous vehicles.

I hold a bachelor’s degree in Instrumentation and Control Engineering from the National Institute of Technology, Tiruchirappalli. I interned for a summer at McMaster University, Canada, with Prof. Gray Bone, where I was involved in the development of an autonomous collaborative robotic arm. I am proficient in C++, Python, and TensorFlow, with a strong publication record in
top-tier robotics and AI conferences.


news

Sep 15, 2025 Excited to share that I’ve joined AlphaZ as the Motion Planning Lead
Aug 26, 2025 I defended my Ph.D. dissertation titled “Safe and Efficient Single- and Multi-Robot Autonomy in Complex Scenarios.
Mar 17, 2025 Delivered a guest lecture in the graduate course CS 6501: Multi-Robot Navigation at the University of Virginia, presenting my research on multi-robot navigation using MPC and reinforcement learning-based approaches.
Feb 10, 2025 This spring, I am working as a Research Intern at Honda Research Institute (HRI), San Jose, focusing on Behavior Modeling and Interactive Planning for Autonomous Vehicles.
Nov 06, 2024 Delivered a talk at Amazon Lab126’s Consumer Robotics Student Summit titled “Navigating the Everyday: Improving Robot Mobility in Household Scenarios.”
Oct 17, 2024 Two papers accepted at IROS 2024: “VLPG-Nav: Object Navigation Using Visual Language Pose Graph and Object Localization Probability Maps” and “When, What, and with Whom to Communicate: Enhancing RL-based Multi-Robot Navigation through Selective Communication.”
May 31, 2023 Spending the summer as an Applied scientist intern at Amazon Lab126, Sunnyvale working on Reliable Object Goal Navigation in household scenes.