Location History:
- Manchester Center, VT (US) (2023)
- Brooklyn, NY (US) (2024)
Company Filing History:
Years Active: 2023-2025
Title: Innovations of Charles Paul Pace
Introduction
Charles Paul Pace is a notable inventor based in Brooklyn, NY, with a remarkable portfolio of seven patents. His work primarily focuses on robotics and autonomous systems, showcasing his commitment to advancing technology in these fields.
Latest Patents
Among his latest innovations is the "Method and system for autonomous object manipulation." This invention involves a robot system capable of manipulating the surface of an object to achieve programmed manipulation goals. These goals include reaching specific locations, displacing the surface, applying predetermined force and torque, dynamically changing contact points, and applying force to structures beneath the object's surface. The system utilizes various sensing methods, including torque and force measurement, visible light sensors, range and depth sensors, ultrasound sensors, thermographic sensors, and worktable force measurement.
Another significant patent is the "Method and system for autonomous body interaction." This system enables a robot to interact with humans or other soft bodies by actively applying pressure to specific points. The method includes localizing the body's position, detecting its configuration, identifying surface regions, predicting underlying anatomy, assessing the body's state, and executing manipulation plans.
Career Highlights
Charles is currently associated with Aescape, Inc., where he continues to innovate and develop advanced robotic systems. His contributions to the field of robotics have positioned him as a key figure in the industry.
Collaborations
Throughout his career, Charles has collaborated with notable individuals such as Eric A Litman and David N Walsh, further enhancing the impact of his work.
Conclusion
Charles Paul Pace's contributions to robotics and autonomous systems reflect his innovative spirit and dedication to technology. His patents demonstrate a profound understanding of complex interactions between robots and their environments, paving the way for future advancements in the field.