Steven Swanbeck
steven dot swanbeck at gmail dot com

I am pursuing my MS in Mechanical Engineering and 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 broadly interested in perception, manipulation, and human-robot interaction.

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, rock climbing, origami, puzzles, and sci-fi novels.

LinkedIn / Github

Updates

Projects

 A Scalable SLAM and Object Extraction Pipeline for Informing Contact and Non-Contact Manipulation Tasks

Steven Swanbeck
Research Project     
Jan 2024 - Present  •   Code (coming soon)

  • Supports custom plugins for image-based predictions and supports fusion of image data with depth images and point clouds generated by robot sensors.
  • A grounded Segment Anything plugin is implemented to extract objects using text inputs.
    • Using behavior trees, the processes associated with data collection, annotation, fusion, and storage can be easily adjusted to fit a desired task, and the stack supports any number of visual data sensors out of the box (subject to computational constraints).

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

    Steven Swanbeck, Daniel Meza, Jared Rosenbaum
    Course Project     
    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 an autonomous mobile robot in real time.

    •  Hylacomylus: Memory Efficient and Robot-Agnostic SLAM for Operation in Large-Scale Environments with Computationally-Limited Hardware

    Steven Swanbeck
    Research Project     
    Jan 2024 - Apr 2024  •   Code (coming soon)

  • Hylacomylus implements pure visual SLAM using KISS-ICP with dynamic data loading and unloading properties to allow comutationally-limited robots to produce and maintain highly-detailed maps of space that remain computationally- and memory-friendly.
  • Produced maps can be effortlessly reloaded into working memory, transferred to other systems for use, or added to.

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

    Steven Swanbeck, Daniel Meza, Jared Rosenbaum, David Fridovich-Keil, Mitch Pryor
    Submitted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)     
    Jan 2024 - Mar 2024  •   Paper (coming soon)

  • GaTORS presents a framework that helps answer the questions of which and how many robots 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.

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

    Frank Regal*, Steven Swanbeck*, Fabian Parra, Mitch Pryor
    ACM/IEEE International Conference on Human-Robot Interaction (HRI '24)     
    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, Jee-Eun Lee
    Course Project     
    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, Jared Rosenbaum
    Course Project     
    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.

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

    Frank Regal, Steven Swanbeck, Fabian Parra, Jared Rosenbaum, Mitch Pryor
    XR-ROB Second International Workshop on "Horizons of Extended Robotics Reality" @ IEEE 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.

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

    Steven Swanbeck
    Research Project
    May 2023 - Present  •   Code (coming soon)

  • 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.

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

    Steven Swanbeck
    Research Project
    May 2023 - Jul 2023  •   Code (coming soon)

  • 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.

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

    Steven Swanbeck, Caleb Horan, Jared Rosenbaum
    Course Project
    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.

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

    Steven Swanbeck, Jared Rosenbaum
    Course Project
    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.

    •  LiDAR & Image Data Fusion for Object Detection with Rapid Labeling and Training Pipeline

    Steven Swanbeck
    Research Project
    Jan 2023 - Jun 2023  •   Code (coming soon)

  • Separate trained LiDAR-based and image-based prediction models are used to make semantic (point-wise/pixel-wise) predictions about the presence of objects of interest within the robot environment.
  • Predictions are fused spatially using projection and probabilistically in the Bayesian sense to predict the locations of these objects in the environment.

    •  Visual Inspection and Mapping Stack for Industrial Survey Applications

    Steven Swanbeck
    Research Project
    Nov 2022 - Mar 2023  •   Code (coming soon)

  • Custom mapping stack developed to create dense 3D representations of robot surroundings using fused 2D image and 3D LiDAR data.
  • Processing functionalities can be easily implemented to localize and ground regions of interest within the environment; map is also used for robot localization as it is developed.

    •  Robotic Street Scam Artist

    Steven Swanbeck, Jared Rosenbaum, Caleb Horan, Alex Macris
    Course Project
    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, 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, 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, Aaron Baker
    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*, 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 quarupedal system capable of teleoperated walking, self-stabilization, and LiDAR mapping of surroundings.

    • * indicates equal contribution