## 1 Introduction  
An anthropomorphic robotic hand (ARH) is an effective gripper for robots, allowing interaction with objects in human\(-\)designed environments. Advancements in 3D printing have made ARH manufacturing feasible and affordable, driving research into improved hardware and control strategies for applications in prosthetics, assistive robotics, and remote operations [1, 2, 3, 4]. ARHs have been developed and utilized for collaborative teleoperation for bimanual manipulations in unstructured tasks [5]. Typically featuring at least 15 finger joints, manually controlling an ARH can be complex, necessitating specialized interface systems to enhance user control. Manipulating an ARH with handheld devices like joystick controllers can be difficult because of the numerous degrees of freedom (DOFs), prompting the use of intuitive hand\(-\)tracking systems. Thus, researchers have developed control interface systems such as hand\(-\)tracking systems [6; 7; 8] and kinematic mapping methods for the telemanipulation of ARHs [4; 9; 10; 11]. Tracking the human thumb is critical in HRI tasks such as telemanipulating an ARH to grasp and manipulate objects [10]. The human thumb is the most complex digit of the hand due to the carpometacarpal (CMC) joint, which plays a significant role in grasping. For available hand\(-\)tracking systems, even though they can track the motion of simple joints with one DOF, most of them either fail to track the motion of the CMC joint or rely on expensive hardware to track its complex motions. Hence, an affordable, personalizable, and easily prototyped tracking device capable of reliably capturing both the CMC joint flexion/extension (FE) and abduction/adduction (AA) motion is necessary for the telemanipulation of a fully actuated thumb. An HRI research platform was developed to investigate, experiment, and develop various interaction modalities for an ARH [12]. The ARH used in this work is based on the InMoov hand [13], where all the digits are underactuated. However, the underactuated InMoov thumb has been replaced with a new thumb with four rotational joints each independently controlled with joint\(-\)attached actuators. Human and robot thumb kinematics differ due to joint configuration, DOFs, and link dimensions. A joint space mapping between the human and robot thumb motion is not desirable, since it produces different poses due to their kinematic differences and makes telemanipulation less intuitive [9]. Thus, a suitable kinematic mapping approach is required for the telemanipulation of the ARH using the tracked thumb motion. In general, a telemanipulation system for a fully actuated robot thumb requires a tracking device capable of capturing the CMC, MCP, and IP joint motions, as well as a kinematic mapping approach to map the human to the robot motion. Also, it is necessary to develop a framework to integrate the functional components of the telemanipulation system to estimate the human thumb pose, establish the mapping between human and robot thumb motion, and actuate the robot thumb. In this research, an affordable, 3D\(-\)printable, personalizable tracking device capable of capturing the complex motion of the human thumb CMC joint is introduced. The tracking device is designed with personalization to ensure proper fitment to different human thumb sizes. The realized device is then employed along with a flex glove to telemanipulate the fully actuated four\(-\)DOF thumb of the developed ARH. The flex glove is a glove outfitted with five (5) bendable variable resistor sensors (flex sensor) and used to track the combined FE motion of the metacarpophalangeal (MCP) and interphalangeal (IP) joints of each finger and thumb. The flex glove is used to telemanipulate the ARH and was developed in our lab [14; 15]. A kinematic model of the human thumb to estimate its joint angles based on the tracking device measurements is presented.