Clare M. Lohrmann

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I am deeply passionate about exploring and enhancing the intricate interplay between humans and robots in collaborative settings. My research focuses on developing innovative solutions that foster effective and intuitive collaboration between humans and robots in dynamic environments, recognizing that these interactions are dyadic in nature - that humans are adapting and updating their beliefs just as we aim to do for robots. I am driven by the belief that robots need to adapt to and work well with all humans, regardless of their abilities or experience. My overarching research goal is to bridge the gap between human belief about robot capabilities and reasoning and the ground truth, enabling them to work seamlessly together as cooperative partners, leveraging their respective strengths to accomplish tasks that neither could do alone. I envision a future where robots are not just tools, but intelligent and adaptable collaborators that are understandable and predictable to those that work with them.

selected publications

2025

  1. Employing Laban Shape for Generating Emotionally and Functionally Expressive Trajectories in Robotic Manipulators
    Srikrishna Bangalore Raghu, Clare Lohrmann, Akshay Bakshi, and 4 more authors
    In 34th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2025), Aug 2025

2024

  1. Iteratively Adding Latent Human Knowledge within Trajectory Optimization Specifications Improves Learning and Task Outcomes
    Christine Chang, Maria Stull, Breanne Crockett, and 4 more authors
    IEEE Robotics and Automation Letters (RA-L), Aug 2024
  2. Generating Pattern-Based Conventions for Predictable Planning in Human-Robot Collaboration
    Clare Lohrmann, Maria Stull, Alessandro Roncone, and 1 more author
    ACM Transactions on Human-Robot Interaction, Mar 2024