Thomas C. Colestock
Papers
1
Total Citations
21
H-Index
1
About
Thomas C. Colestock is a researcher advancing the frontiers of robotic manipulation, with a primary focus on tactile sensing, adaptive grasp control, and human-robot collaboration. His most cited work, “Direction of Slip Detection for Adaptive Grasp Force Control with a Dexterous Robotic Hand” (2018, 21 citations), introduces a novel method for tactile communication within collaborative teams—both human-robot and robot-robot. By applying neural networks to classify the direction of object slippage against tactile fingertips, Colestock’s research enables dexterous robotic hands to dynamically adjust grip force, a critical capability for safe and effective manipulation in unstructured environments. This contribution addresses a fundamental challenge in robotics: achieving the delicate balance between secure grasping and gentle handling. Though early in his citation impact, his work lays essential groundwork for more intuitive and responsive robotic systems. Colestock’s investigations sit at the intersection of machine learning, sensor design, and control theory, promising to enhance the autonomy and reliability of robots in applications ranging from manufacturing to assistive care.
Research Focus
Key Achievements
Top Papers
- 1