Design and Evaluation of a Compact 3D End-effector Assistive Robot for Adaptive Arm Support

TL;DR

This work presents a compact 3D end-effector assistive robot (ARAE) designed for home-based upper-limb therapy, featuring a parallel mechanism with 3 active and 2 passive joints and quasi-direct-drive actuation. An adaptive gravity compensation framework estimates user posture using two sensor-free joint-angle estimation methods (fixed-torso and sagittal-plane models) to compute a compensatory force that is mapped to robot torque, enhancing transparency and reducing muscular effort during ADLs. Experimental results show the sagittal-plane model yields slightly better angle-estimation accuracy (MAE around 5.37°) and that the adaptive GC framework significantly reduces EMG activity across tasks, supporting the potential for home-based rehabilitation in real environments. The findings highlight the system’s usability and effectiveness, while outlining future work on personalization and broader patient testing, including stroke populations.

Abstract

We developed a 3D end-effector type of upper limb assistive robot, named as Assistive Robotic Arm Extender (ARAE), that provides transparency movement and adaptive arm support control to achieve home-based therapy and training in the real environment. The proposed system composes five degrees of freedom, including three active motors and two passive joints at the end-effector module. The core structure of the system is based on a parallel mechanism. The kinematic and dynamic modeling are illustrated in detail. The proposed adaptive arm support control framework calculates the compensated force based on the estimated human arm posture in 3D space. It firstly estimates human arm joint angles using two proposed methods: fixed torso and sagittal plane models without using external sensors such as IMUs, magnetic sensors, or depth cameras. The experiments were carried out to evaluate the performance of the two proposed angle estimation methods. Then, the estimated human joint angles were input into the human upper limb dynamics model to derive the required support force generated by the robot. The muscular activities were measured to evaluate the effects of the proposed framework. The obvious reduction of muscular activities was exhibited when participants were tested with the ARAE under an adaptive arm gravity compensation control framework. The overall results suggest that the ARAE system, when combined with the proposed control framework, has the potential to offer adaptive arm support. This integration could enable effective training with Activities of Daily Living (ADLs) and interaction with real environments.

Figures (11)

• Figure 1: Proposed system. (a). A healthy subject is attached with ARAE prototype. (b). The mechanical structure of ARAE.
• Figure 2: Flow chart of the robotic system
• Figure 3: Schematic combined with human arm and ARAE robotic system. The human arm is modeled as a four degree of freedom link mechanism, including $3$ revolute joints at the shoulder joint and $1$ revolute joint at the elbow joint ($\textbf{E}$) under the human shoulder base coordinate $O_{S}$. The human shoulder base frame is denoted as {$O_{S}$}:$O_{S} - x_{S}y_{S}z_{S}$. $\boldsymbol{S}, \boldsymbol{E}$ and $\boldsymbol{W}$ represent the position vector of the shoulder joint, elbow joint, and wrist joint under the human shoulder base coordinate
• Figure 4: The system control framework demonstrates the interaction between the human and robot systems. The human system mainly refers to the proposed adaptive GC of the human arm control framework. Firstly, to estimate the human joint angles $h_j$ based on the $\textbf{P}_s, \textbf{P}_e$ and $\textbf{P}_w$ obtaining from the fixed torso model or sagittal plane model. Secondly, calculate the human arm needed support force $F_h$, then transmit to the torque provided by the robot $\tau_{h}$. The reference torque $\tau_{ref}$ is fed into the motor controller of robot system $\tau_{ref} = \tau_c + \tau_R$. $\tau_R$ is the gravity torque of the robot structure.
• Figure 5: Schematic diagram for obtaining the shoulder position. The COM of the pelvis is the original point of the pelvis base coordinate {$O_{hp}$}:$O_{hp} - x_{hp}y_{hp}z_{hp}$. $\textbf{E'}$ is the projection of the elbow joint in the sagittal plane. $H$ represents the hip joint which is located at the sagittal plane and $x_P$ axis