Rachel Holladay
Massachusetts Institute of Technology, Carnegie Mellon University
Papers
13
Total Citations
1,013
H-Index
11
About
Rachel Holladay is a leading roboticist whose research lies at the intersection of manipulation, human-robot interaction, and task planning. Her most influential work, the multi-award-winning "Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching" (over 700 combined citations), revolutionized robotic grasping by enabling systems to handle a vast range of unknown objects without task-specific training data. She has also made seminal contributions to assistive robotics, developing time-optimal mode-switching algorithms that empower users with disabilities to control dexterous robotic arms using simple interfaces (105 citations). Holladay’s work on legible and deceptive robot motion (90+ citations) fundamentally advanced how robots communicate intent through gestures and even strategic deception, a critical capability for natural human-robot collaboration. Her recent research on force-and-motion constrained planning for tool use and multi-stage forceful manipulation (e.g., opening childproof bottles) tackles the challenging intersection of discrete task reasoning and continuous force application. As a key contributor to the integrated task and motion planning framework, Holladay continues to push the boundaries of what robots can achieve in complex, real-world environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Assistive teleoperation of robot arms via automatic time-optimal mode switching105 citations · 2016
- 4Legible robot pointing54 citations · 2014
- 5
- 6Force-and-Motion Constrained Planning for Tool Use37 citations · 2019
- 7An Analysis of Deceptive Robot Motion36 citations · 2014
- 8Deceptive robot motion: synthesis, analysis and experiments26 citations · 2015
- 9Integrated Task and Motion Planning17 citations · 2021
- 10Robust planning for multi-stage forceful manipulation13 citations · 2023