Kyle Schroeder

About

Kyle Schroeder’s research lies at the intersection of trustworthy AI, robotic safety, and energy-efficient legged locomotion. His work addresses critical challenges in deploying robots in high-risk environments, where human trust and system reliability are paramount. Schroeder’s most cited paper, “AI Augmentation for Trustworthy AI: Augmented Robot Teleoperation” (11 citations), explores how AI can enhance human-robot collaboration without fully removing humans from the loop—a key concern in sectors like healthcare and manufacturing. He also made significant contributions to industrial robot safety with “An Extended Kalman Filter for Collision Detection During Manipulator Contact Tasks” (7 citations), integrating software compliance and collision detection to enable safer operation in unstructured settings. In legged robotics, Schroeder’s work on optimal stiffness design and parallel actuation (4 and 2 citations, respectively) tackles the energy efficiency gap between biological systems and state-of-the-art robots. His research on mechanical antagonism and power-optimal pseudoinverses (2 citations) further advances efficient actuation. With a focus on practical, real-world applications, Schroeder’s work is shaping the future of trustworthy, safe, and energy-efficient robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   AI Augmentation for Trustworthy AI: Augmented Robot Teleoperation

   11 citations · 2020
2. 2
   An Extended Kalman Filter for Collision Detection During Manipulator Contact Tasks

   7 citations · 2014
3. 3
   Optimal Stiffness Design for an Exhaustive Parallel Compliance Matrix in Multiactuator Robotic Limbs

   4 citations · 2018
4. 4
   Advanced Parallel Actuation of a Serial Robotic Leg

   2 citations · 2016
5. 5
   Understanding Power Loss due to Mechanical Antagonism and a New Power-Optimal Pseudoinverse for Redundant Actuators

   2 citations · 2017

Key Collaborators

Contact & Links