Shannon Enders
Papers
1
Total Citations
3
H-Index
1
About
Shannon Enders is a robotics researcher whose work centers on flexible manipulation and human-robot collaboration, with a particular focus on developing intuitive, adaptive control systems. Her most cited paper, "Flexible Manipulation: Finite State Machine-based Collaborative Manipulation" (2018), introduces a novel approach that integrates the Robot Operating System (ROS) with MoveIt! planning and the Flexible Behavior Engine (FlexBE). This work provides enhanced MoveIt! capabilities and associated FlexBE state implementations, enabling more fluid and responsive robotic manipulation in collaborative settings. While her citation count is modest—with 3 citations for this key paper—her contributions are significant in advancing practical, modular frameworks for robot behavior control. Enders’ research bridges the gap between high-level task planning and low-level motion execution, making complex manipulation more accessible for real-world applications. Her work is particularly valuable for students and researchers exploring ROS-based systems, finite state machines, and human-robot interaction, offering a foundation for building more adaptable and user-friendly robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1