Human-Robot Collaboration

Humans are hard to model and predict; thus, it is hard for a robot to consider how other people in the environment may act in its decision-making process. Finding efficient and effective ways to model human behavior to maintain the safety of people around a robot or to allow a robot to fluently collaborate with other people (or perhaps even other agents) is critical to deploying robots outside controlled environments such as the lab or factory.

Moreover, as robots become more capable agents and enter the real world, systems today appear in the workplace, home, and public spaces. Ethical considerations of how robots should operate are trailing behind algorithmic advances, and these advances do not necessarily consider the other people the robot is working around explicitly. Suppose the algorithms that control a robot’s behavior are agnostic to human concerns. In that case, they will be (un)intentionally exploited by malicious, unethical, or ignorant actors to violate privacy, injure and disturb people, and further increase inequity.


2024

  1. Abstract
    Perception-aware Planning for Robotics: Challenges and Opportunities
    In 40th Anniversary of the IEEE Conference on Robotics and Automation (ICRA@40)
  2. Workshop
    Monitoring Constraints for Robotic Tutors in Nurse Education: A Motion Planning Perspective
    Qingxi Meng*Carlos Quintero-Peña*Zachary Kingston , Nicole M. Fontenot , Shannan K. Hamlin , and 2 more authors
    In IEEE ICRA 2024 Workshop—Workshop on Nursing Robotics

2023

  1. Robots as AI Double Agents: Privacy in Motion Planning
    In IEEE/RSJ International Conference on Intelligent Robots and Systems

2021

  1. Finite Horizon Synthesis for Probabilistic Manipulation Domains
    In IEEE International Conference on Robotics and Automation