Zac Ravichandran

ZacRavichandran_Headshot1_cut.jpg

Hi! I’m a second-year PhD Student in The GRASP Lab at The University of Pennsylvania, where I’m co-advised by Vijay Kumar and George J. Pappas. I’m gratefully supported by the NSF Graduate Research Fellowship.

My research focuses on developing robots with advanced contextual reasoning abilities, enabling them to understand natural language, actively gather mission-relevant information, and intelligently collaborate within a team. Additionally, my work investigates and addresses the safety implications of AI-enabled robotics, particularly those using large language models or other foundation models.

You can reach me at zacravi [at] seas [dot] upenn [dot] edu

publications

2025

  1. In review
    Safety Guardrails for LLM-enabled Robots
    Zachary Ravichandran, Alexander Robey, Vijay Kumar, George J. Pappas, and Hamed Hassani
    arXiv preprint arXiv:2503.07885, 2025
  2. ICRA 25
    Jailbreaking LLM-Controlled Robots
    Alexander Robey, Zachary Ravichandran, Vijay Kumar, Hamed Hassani, and George J. Pappas
    International Conference on Robotics and Automation, 2025
  3. ICRA 25
    SPINE: Online Semantic Planning for Missions with Incomplete Natural Language Specifications in Unstructured Environments
    Zachary Ravichandran, Varun Murali, Mariliza Tzes, George J. Pappas, and Vijay Kumar
    International Conference on Robotics and Automation, 2025

2024

  1. ICRA 24 WS
    Challenges and Opportunities for Large-Scale Exploration with Air-Ground Teams using Semantics
    Fernando Cladera, Ian D Miller, Zachary Ravichandran, Varun Murali, Jason Hughes, M Ani Hsieh, CJ Taylor, and Vijay Kumar
    International Conference on Robotics and Automation Workshops, 2024
  2. ICRA 24
    Enabling Large-scale Heterogeneous Collaboration with Opportunistic Communications
    Fernando Cladera, Zachary Ravichandran, Ian D Miller, M Ani Hsieh, CJ Taylor, and Vijay Kumar
    International Conference on Robotics and Automation, 2024

2022

  1. ICRA 22
    Hierarchical Representations and Explicit Memory: Learning Effective Navigation Policies on 3D Scene Graphs using Graph Neural Networks
    Zachary Ravichandran, Lisa Peng, Nathan Hughes, J. Daniel Griffith, and Luca Carlone
    International Conference on Robotics and Automation, 2022

2020

  1. Tech. Report
    Bridging Task Execution and Scene Understanding with Flexible Simulation Environments
    Zachary Ravichandran, J. Daniel Griffith, Benjamin Smith, and Constantine Frost
    Technical Report, Nov 2020