Fadhil Ginting

Muhammad Fadhil Ginting

I am a PhD candidate in AI Robotics at Stanford University advised by Prof. Mykel Kochenderfer in the Stanford Intelligent System Laboratory (SISL), part of the Stanford Artificial Intelligence Laboratory (SAIL). My research is supported by the Stanford Graduate Fellowship and in collaboration with NASA Jet Propulsion Laboratory (JPL) and a robotics startup Field AI.

Before joining Stanford, I was a visiting researcher at NASA JPL for two years and was one of the key members in the JPL-led team for the DARPA Subterranean Challenge that won the 2020 DARPA Subterranean Challenge Urban Circuit .

I completed my Master’s degree in Robotics at ETH Zurich. I received a Bachelor of Science in Electrical Engineering from Institut Teknologi Bandung, graduating as the valedictorian.

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Updates

[June 2024] Our paper on semantic-aware object search got accepted to IROS 2024.
[June 2024] Our work is featured in IEEE Spectrum's Video Friday.
[May 2024] Our paper on semantic reasoning for object goal navigation got accepted to RSS 2024!
[January 2024] I gave a research talk at Stanford AA 229 course.
[October 2023] I presented a poster at BARS.
[June 2023] I started a research internship at Field AI.
[May 2023] I passed the Stanford PhD qualifying exam!
[January 2023] Our work on locomotion adaptation with semantic belief graph is accepted to ICRA 2023.
[June 2022] Our work on capability-aware task allocation got accepted to IROS 2022.
[October 2021] I gave a talk on lessons learned in the SubT Challenge at Stanford MSL.
[September 2021] Excited to start my PhD at Stanford!

Research

My research interests lie in enabling embodied AI for robots to navigate and interact with unstructured environments using risk-aware autonomy and large foundation models.

I am a full-stack roboticist with experience in developing cutting-edge algorithms for perception, planning, control, and communication, as well as deploying robots in the field for real-world use cases.

	SEEK: Semantic Reasoning for Object Goal Navigation in Real World Inspection Tasks Muhammad Fadhil Ginting, Sung-Kyun Kim, David Fan, Matteo Palieri, Mykel Kochenderfer, Ali-akbar Agha-mohammadi Robotics: Science and Systems, 2024 Arxiv We propose a probabilistic planning method for object-goal navigation that uses relational semantic knowledge and prior spatial configuration for real-world inspection.
	Semantic Belief Behavior Graph: Enabling Autonomous Robot Inspection in Unknown Environments M. F. Ginting, D. D. Fan, S. K. Kim, M. J. Kochenderfer, and A. Agha-mohammadi IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024 Arxiv We propose a belief-space task planning framework for semantic-based navigation in real world inspection.
	Safe and Efficient Navigation in Extreme Environments using Semantic Belief Graphs M. F. Ginting, S. K. Kim, O. Peltzer, J. Ott, S. Jung, M. J. Kochenderfer, and A. Agha-mohammadi IEEE International Conference on Robotics and Automation (ICRA), 2023 Arxiv
	Capability-Aware Task Allocation and Team Formation Analysis for Cooperative Exploration of Complex Environments M. F. Ginting, K. Otsu, M. J. Kochenderfer, and A. Agha-mohammadi IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022 Paper
	LAMP 2.0: A Robust Multi-Robot SLAM System for Operation in Challenging Large-Scale Underground Environments Y. Chang, K. Ebadi, C. E. Denniston, M. F. Ginting, A. Rosinol, A. Reinke, M. Palieri, J. Shi, A. Chatterjee, B. Morrell, A. Agha-mohammadi, L. Carlone IEEE Robotics and Automation Letters (RA-L), 2022 Arxiv
	Autonomous Mapping and Characterization of Terrestrial Lava Caves Using Quadruped Robots: Preparing for a Mission to a Planetary Cave J. G. Blank, B. Morrell, A. Bouman, T. Touma, M. F. Ginting, C. Patterson, A. Agha-mohammadi Workshop on Terrestrial Analogs for Planetary Exploration, 2021
	Nebula: Quest for Robotic Autonomy in Challenging Environments; Team CoSTAR at the DARPA Subterranean Challenge Journal of Field Robotics, 2021 Arxiv
	CHORD: Distributed Data-sharing via Hybrid ROS 1 and 2 for Multi-robot Exploration of Large-scale Complex Environments M. F. Ginting, K. Otsu, J. A. Edlund, J. Gao, and A. Agha-Mohammadi IEEE Robotics and Automation Letters (RA-L), 2021 Paper
	Copilot MIKE: An Autonomous Assistant for Multi-Robot Operations in Cave Exploration M. Kaufmann, T. S. Vaquero, G. J. Correa, K. Otsu, M. F. Ginting, G. Beltrame, A. Agha-Mohammadi IEEE Aerospace Conference, 2021 Paper
	Autonomous Spot: Long-range Autonomous Exploration of Extreme Environments with Legged Locomotion M. F. Ginting, A. Bouman, N. Alatur, M. Palieri, D. D. Fan, T. Touma, T. Pailevanian, S. K. Kim, K. Otsu, J. Burdick, and A. Agha-Mohammadi IEEE International Conference on Intelligent Robots and Systems (IROS), 2020 Best Paper Award on Safety, Security, and Rescue Robotics* Paper

Media Coverage

	Interns Lead the Way in DARPA Robotics Challenge and Find Their Futures
	How JPL's Team CoSTAR Won the DARPA SubT Challenge: Urban Circuit Systems Track
	Meet Au-Spot, the AI robot dog that's training to explore caves on Mars
	Robots Autonomously Navigate Underground in DARPA Challenge

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