KATHRYN LAMPO
Teleoperated Robotic Gripper & Controller 📞👋 Robotic Manipulation and Mobility (ROAM) Laboratory, Columbia University | Spring 2024
Collaborators: Philippe Wu | Advisors: Joaquin Palacios, Gagan Khandate, Matei Ciocarlie

 With the goal of developing a low-cost testing platform for the lab, this project focued on building on the work of the ALOHA team to create a teleoperated robotic gripper. Our aim was to enable robots to complete dexterous bi-manual manipulation tasks using accessible hardware and imitation learning, negating the need for expensive sensors, vision systems, or closed-loop feedback.



The system consists of two parts: a human-operated controller and a robotic end-effector that attaches to the lab’s UR5 arm. Motion from the controller is mapped directly to the end-effector, allowing human participants to model tasks for the robot to learn. Further details about various aspects of the project are given below:

  • Controller: Taking a human-centered design approach, we developed a controller akin to a pair of kitchen tongs. Operable with one hand, the controller is the same size as the end-effector, and is constrained by a 80/20 rail to ensure linear motion.

  • End-Effector: The end-effector is built around a Dynamixel servo and uses a custom-designed linkage to convert rotational motion into translational grasping. The linkage is torque-optimized and ensures that the fingers can start and stop from any position. 

  • Fingers: Designed to be modular, the “fingers” (white in the GIF to the right) are hot-swappable for different applications. During the design process, we fabricated both PLA and TPU versions, providing stiff and pliable options.

  • Motion Tracking: In our design, motion is tracked using a Trackstar positioning system (for absolute location) and a 1-turn rotational potentiometer (for opening/closing the gripper). The potentiometer is embedded into the base of the controller along with a torsional spring that provides tactile resistance to the user.

  • Control: As a preliminary method of control, we used serial communication between an Arduino board (controller) and OpenRB-150 board (end-effector). The voltage values from the potentiometer were mapped linearly to the effective range of the angular position on the end effector, allowing for the motion shown here. In the time since, the project has switched to control using ROS1.
In the time since this project, the system has been modified and used in the lab for some cool research, including the two publications below!

VibeCheck: Using Active Acoustic Tactile Sensing for Contact-Rich Manipulation
Kaidi Zhang*, Do-Gon Kim*, Eric T. Chang*, Hua-Hsuan Liang, Zhanpeng He, Kathryn Lampo, Philippe Wu, Ioannis Kymissis, Matei Ciocarlie
IROS 2025 (accepted)
arXiv

Train Robots in a JIF: Joint Inverse and Forward Dynamics with Human and Robot Demonstrations
Gagan Khandate*, Boxuan Wang*, Sarah Park*, Weizhe Ni, Joaquin Palacios, Kathryn Lampo, Philippe Wu, Rosh Ho, Eric Chang, Matei Ciocarlie
arXiv
kathrynlampo@gmail.com |