Steven Swanbeck
stevenswanbeck at gmail dot com

I am pursuing my PhD in Robotics at The University of Texas at Austin advised by Dr. Mitch Pryor in the Nuclear and Applied Robotics Group (NRG). I am passionate about developing robotic systems that assist humans to solve our greatest challenges. I am fascinated by many facets of robotics and have broad experience in perception, manipulation, and human-robot interaction. As of now, I am most interested in the development of approaches and tools that improve the ability of robotic systems to scale across embodiments, tasks, and environments.

Previously, I completed my BS in Mechanical Engineering from the University of Nevada, Reno, advised by Dr. Jun Zhang in the Smart Robotics Lab.

Aside from robotics, I also enjoy basketball, running, rock climbing, origami, puzzles, and sci-fi novels.

LinkedIn / Github

Updates

Projects

 Coral: A Unifying Abstraction Layer for Compositional Robotics Software

Steven Swanbeck and Mitch Pryor
IEEE/SICE International Symposium on System Integration (SII 2026)     
Dec 2024 - Sep 2025  •   Paper (coming soon)  •  Code

  • Coral emphasizes compositionality as a first-class design principle to simplify the integration and deployment of complex robotics software systems.
  • Use of behavior trees, robotics middleware, and containerization as intermediate abstractions promotes compositionality across both the system and task levels.

    •  Fighting Rust with Robots: Toward Scalable Corrosion Mitigation in Industrial Environments Using Robotic Systems

    Steven Swanbeck, Jared Rosenbaum, Jorge A. Diaz, Fabian Parra Gil, and Mitch Pryor
    IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2025)   •   Best Paper Finalist
    Aug 2023 - Jul 2025  •   Paper (coming soon)

  • Corrosion of steel infrastructure presents one of the most economically and environmentally costly problems faced by humanity.
  • Using robotic systems for environment surveying, augmented reality interfaces to bring human supervisors into the loop, and both mobile and static high-reach manipulators for surface coverage, we demonstrate an approach to scalable autonomous corrosion mitigation.

    •  Hyla-SLAM: Toward Maximally Scalable 3D LiDAR-Based SLAM Using Dynamic Memory Management and Behavior Trees

    Steven Swanbeck and Mitch Pryor
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025)     
    Aug 2024 - Mar 2025  •   Paper  •  Code

  • Hyla-SLAM dynamically discretizes and loads/unloads map data during runtime to efficiently create, expand, and manage extremely large maps (up to 7.4e09 cubic light years in volume) on resource-constrained (and potentially distributed) systems.
  • Hyla-SLAM also provides a behavior tree interface, allowing for flexible creation of task- or robot-specific SLAM loops that can easily incorporate other behavior-based capabilities.

    •  No Reboot Required: Real-Time Modular Robot Payload Integration

    Jonathan Salfity, Corrie Van Sice, Benjamin Chen, Steven Swanbeck, Robert Blake Anderson, and Mitch Pryor
    International Conference on Ubiquitous Robots (UR 2025)     
    Jan 2025 - Mar 2025  •   Paper

  • In contrast to the traditional robotics system engineering practice of creating monolithic systems that require a high amount of engineering effort to modify, we demonstrate a preliminary approach that allows a robot to incorporate new payloads (an RGB camera and image detection model) online in real time with no developer intervention and immediately utilize them in task planning and execution.

    •  GaTORS: A Game-Theoretic Tool for Optimal Robot Platform Selection and Design in Surface Coverage Applications

    Steven Swanbeck, Daniel I. Meza, Jared Rosenbaum, David Fridovich-Keil, and Mitch Pryor
    International Conference on Ubiquitous Robots (UR 2025)     
    Jan 2024 - Apr 2024  •   Paper   •  Code

  • GaTORS helps answer the questions of which and how many robots drawn from a heterogeneous fleet should be deployed in real world environments to complete surface coverage tasks.
  • The design of systems can also be optimized by performing systematic parameter sweeps over the space of possible configurations to set targets to achieve economic viability.

    •  Autonomous Obstacle Avoidance, Localization, Navigation, and SLAM on a Mobile Robot

    Steven Swanbeck, Daniel Meza, and Jared Rosenbaum
    Course Project (CS 393R Autonomous Robots @ UT Austin)     
    Jan 2024 - Apr 2024  •   Code

  • Simple obstacle avoidance, particle filter-based localization, navigation using RRT* for global planning and a line-of-sight carrot planner for local planning, and SLAM using correlative scan matching and GTSAM for pose graph optimization implemented to run onboard a small autonomous mobile robot in real time.

    •  AR-STAR: An Augmented Reality Tool for Online Modification of Robot Point Cloud Data

    Frank Regal*, Steven Swanbeck*, Fabian Parra Gil, and Mitch Pryor
    ACM/IEEE International Conference on Human-Robot Interaction (HRI 2024)     
    Oct 2023 - Dec 2023  •   Paper

  • Uncertainty in sensor data collected onboard a deployed robot can hinder its ability to complete a mission, and it can be difficult for a robot to autonomously detect and overcome these uncertainties.
  • We develop an augmented reality tool that allows a a human supervisor to visualize a robot's predictions and modify them online using one of three interaction modalities and study user preferences in using them.

    •  Reinforcement Learning for Traversal of Uncertain Vertical Terrain using a Magnetic Wall-Climbing Robot

    Steven Swanbeck and Jee-Eun Lee
    Course Project (ASE 389 Learning for Dynamics and Control @ UT Austin)     
    Sep 2023 - Dec 2023  •   Code

  • Using only its own kinematics, magnetic forces experienced at its feet, and a goal position, a magnetic wall climbing robot is trained to navigate a surface within unknown and irregular magnetic properties.
  • Developed a custom ROS-based bridge to interface the C++ simulation toolkit DART with Python RL libraries and trained Deep Q-Learning and PPO policies using it.

    •  Game-Theoretic Modeling for Robot Platform Selection in Industrial Repair Applications

    Steven Swanbeck, Daniel Meza, and Jared Rosenbaum
    Course Project (ASE 389 Game-Theoretic Modeling of Multi-Agent Systems @ UT Austin)     
    Oct 2023 - Dec 2023  •   Code

  • Using game-theoretic modeling, the ability of different robotic hardware platforms to perform maintenance and inspection tasks in a shared environment is evaluated.
  • With this competitive modeling approach, the ability to select a minimally-sized heterogeneous robot team to accomplish comprehensive corrosion repairs within predefined budget and time constraints in complex industrial environments was demonstrated.

    •  Non-Contact Surface Coverage of Corroded Material in Industrial Environments

    Steven Swanbeck
    Research Project
    Aug 2023 - Dec 2023

  • Surface identification used to extract the locations and geometries of possible corroded surfaces within industrial environments.
  • Coverage planning and execution with constraint-relaxed redundant replanning enables coverage over the identified surfaces using a mobile manipulator system with a protective spray coating, preventing further corrosion development.

    •  Using Augmented Reality to Assess and Modify Mobile Manipulator Surface Repair Plans

    Frank Regal, Steven Swanbeck, Fabian Parra Gil, Jared Rosenbaum, and Mitch Pryor
    International Workshop on Horizons of Extended Robotics Reality (@ IROS 2023)  •   Second Prize
    Jul 2023 - Aug 2023  •   Paper

  • Using an AR head-mounted display, a user is able to view predictions made by a surveying robot for surface repair.
  • The user can accept, reject, or modify the plan generated by the robot to prevent incidental covering of sensitive material or repair of unproblematic surfaces.

    •  Virtual Fixture Generation and Execution for Surface Coverage of Complex Geometries

    Steven Swanbeck
    Research Project
    May 2023 - Jul 2023

  • Using computer vision models, LiDAR detection models, or supervised scene labeling, surfaces on which a robot should perform surface inspection are denoted.
  • A discrete pose mesh is created offset from the surface that can be traversed using a manipulator to perform the surface coverage task.

    •  A MATLAB Toolbox using Screw Theory for Forward and Inverse Kinematics of Manipulators

    Steven Swanbeck
    Course Project (ME 397 Algorithms for Sensor-Based Robotics @ UT Austin)
    Feb 2023 - April 2023  •   Code

  • Robots of arbitrary structure can be defined and visualized using screw theory.
  • Space frame and body frame forward kinematics can be calculated and visualized and manipulability measures are calculated and monitored.
  • Various inverse kinematics algorithms, including Jacobian pseudo-inverse, Jacobian transpose, redundancy resolution, and damped least-squares are available.

    •  Bat-Inspired Passive Drone Gripper for Angle-Invariant Perching

    Steven Swanbeck
    Course Project (ME 380R Robot Mechanism Design @ UT Austin)
    March 2023 - April 2023  •   Code

  • A custom mechanism inspired by the passive inverted hanging ability of bats to allow a drone to remain perched in one location for long periods of time without expending battery power.
  • In addition to perching in upright or inverted orientations, the gripper can also be used as landing gear for the drone or for holding objects during flight.

    •  Robotic Street Scam Artist

    Steven Swanbeck
    Course Project (ME 396P Application Programming for Engineers @ UT Austin)
    Oct 2022 - Nov 2022  •   Code

  • Combining manipulator control and computer vision, an eye-in-hand system is able to localize and track a series of shells as they are shuffled, inspect each to look for a planted marker, and pick it to reveal the money in a modified version of the classic street scam shell game.
  • Hand-tracking using the manipulator and writing calculation results also developed as intermediate steps.

    •  Kinematic Modeling of a Twisted-String Actuated Soft Robotic Finger as Part of an Anthropomorphic Gripper

    Steven Swanbeck, Revanth Konda, and Jun Zhang
    Modeling, Estimation, and Control Conference (MECC 2023)
    Apr 2022 - Aug 2022  •   Paper

  • Modeling strategies for a twisted-string actuator-driven soft robotic gripper developed to enable control and autonomous capabilities.

    •  STAR–2: A Soft Twisted-string-actuated Anthropomorphic Robotic Gripper: Design, Fabrication, and Preliminary Testing

    Aaron Baker, Claire Foy, Steven Swanbeck, Revanth Konda, and Jun Zhang
    IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2023)
    Mar 2022 - Aug 2022  •   Paper

  • 2.0 version of previous soft gripper with increased range-of-motion and degrees-of-freedom.

    •  Dexterous Soft Gripper Manipulator Integration for Human-Robot Interaction

    Steven Swanbeck
    Research Project
    Feb 2022 - Aug 2022  •   Code

  • Enhanced version of anthropomorphic gripper with 5 additional degrees of freedom integrated with a UR3e manipulator.
  • ROS integration allowed for coordinated control of gripper and manipulator, enabling pick-and-place and human-robot interaction demonstrations.

    •  Anthropomorphic Twisted String-Actuated Soft Robotic Gripper With Tendon-Based Stiffening

    Revanth Konda*, David Bombara*, Steven Swanbeck*, and Jun Zhang
    IEEE Transactions on Robotics (April 2023)
    Sep 2021 - Feb 2022  •   Paper

  • Soft gripper capable of mimicking many of the grasping capabilities of the human hand, including achieving 31/33 grasps of the Feix GRASP Taxonomy and resisting a maximum force of 72N, over 13 times its own weight.

    •  Sublunar Lava Tube Exploration Quadruped

    Steven Swanbeck
    NASA University Student Design Challenge
    May 2021 - Aug 2021  •   Code

  • Project to design a robotic system capable of surveying lava tubes under the surface of the moon to assess their ability to sustain long-term human habitation.
  • Custom quadrupedal system capable of teleoperated walking, self-stabilization, and LiDAR mapping of surroundings.

    • * indicates equal contribution