Supernumerary robotic limbs (SRL) are new types of wearable robots used as the third limb to work with humans. The device is designed to provide the wearer with better auxiliary ability. This paper presents the design and implementation of a Series-Parallel-Reconfigurable Tendon-driven Supernumerary Robotic Arms (RTSRAs), which is lightweight, compact and Multi-assistive for the wearers. Existing Supernumerary robotic limbs (SRL) devices almost use series configurations with high flexibility, but relatively poor carrying capacity compared to parallel configurations. Balancing the contradiction between load capacity and flexibility, we propose a Series-Parallel-Reconfigurable configuration requiring clever end-conversion tools to better adapt to variable tasks. To achieve the compactness of RTSRAs, two kinds of tendon-driven joint module were designed. The coupled tendon-driven joint module was applied to transmit the power of motors mounted near the backboard to the elbow joints, which greatly reduce the motion inertia and increase load capacity of RTSRAs. Finally, on the basis of forward and inverse kinematics analysis, we make the evaluation of RTSRAs. The proposed RTSRAs has been successfully applied in typical load operation scenario and suggests a great potential in future applications.

Mixed reality technology can give humans an intuitive visual experience, and combined with the multi-source information of the human body, it can provide a comfortable human–robot interaction experience. This paper applies a mixed reality device (Hololens2) to provide interactive communication between the wearer and the wearable robotic limb (supernumerary robotic limb, SRL). Hololens2 can obtain human body information, including eye gaze, hand gestures, voice input, etc. It can also provide feedback information to the wearer through augmented reality and audio output, which is the communication bridge needed in human–robot interaction. Implementing a wearable robotic arm integrated with HoloLens2 is proposed to augment the wearer’s capabilities. Taking two typical practical tasks of cable installation and electrical connector soldering in aircraft manufacturing as examples, the task models and interaction scheme are designed. Finally, human augmentation is evaluated in terms of task completion time statistics.

The Wearable Robotic Limb (WRL) is a type of robotic arm worn on the human body, aiming to enhance the wearer’s operational capabilities. However, proposing additional methods to control and perceive the WRL when human limbs are heavily occupied with primary tasks presents a challenge. Existing interactive methods, such as voice, gaze, and electromyography (EMG), have limitations in control precision and convenience. To address this, we have developed an interactive device that utilizes the mouth and tongue. This device is lightweight and compact, allowing wearers to achieve continuous motion and contact force control of the WRL. By using a tongue controller and mouth gas pressure sensor, wearers can control the WRL while also receiving sensitive contact feedback through changes in mouth pressure. To facilitate bidirectional interaction between the wearer and the WRL, we have devised an algorithm that divides WRL control into motion and force-position hybrid modes. In order to evaluate the performance of the device, we conducted an experiment with ten participants tasked with completing a pin-hole assembly task with the assistance of the WRL system. The results show that the device enables continuous control of the position and contact force of the WRL, with users perceiving feedback through mouth airflow resistance. However, the experiment also revealed some shortcomings of the device, including user fatigue and its impact on breathing. After experimental investigation, it was observed that fatigue levels can decrease with training. Experimental studies have revealed that fatigue levels can decrease with training. Furthermore, the limitations of the device have shown potential for improvement through structural enhancements. Overall, our mouth and tongue interactive device shows promising potential in controlling the WRL during tasks where human limbs are occupied.

Supernumerary robotic limbs (SRLs) are wearable robots that serve as extra limbs, assisting wearers in task completion. The strong coupling between SRLs and wearers results in wearer movements influencing SRLs' actions and the forces exerted on mechanisms during operations. The wearer's movements lead to uncertain and uncontrollable base movements, making operational control of the SRLs challenging. This study proposes a full-process assisted door-opening method using SRLs, integrating a task model and an anti-disturbance door-opening controller. Multimodal information from the SRLs system is utilized to facilitate task state transitions. The anti-disturbance door-opening controller consists of compliant controller, online identification of mechanism characteristics, end-effector trajectory generator, and notch filter. This method enables the SRLs to complete the door-opening task under motion disturbances caused by the wearer, without prior knowledge of the door's resistance, radius, or axis direction. Experimental results show that the SRLs can successfully open doors, with estimates converging to actual values under various radius and axis direction conditions (with radius estimation error less than 0.01m and axial estimation error less than 3.8 $^{\circ }$ ). The effectiveness of the proposed control framework is validated in daily environments.

Supernumerary Robotic Limbs (SRLs) are designed to collaborate with the wearer, enhancing operational capabilities. When human limbs are occupied with primary tasks, controlling SRLs flexibly and naturally becomes a challenge. Existing methods such as electromyography (EMG) control and redundant limb control partially address SRL control issues. However, they still face limitations like restricted degrees of freedom and complex data requirements, which hinder their applicability in real-world scenarios. Additionally, fully autonomous control methods, while efficient, often lack the flexibility needed for complex tasks, as they do not allow for real-time user adjustments. In contrast, shared control combines machine autonomy with human input, enabling finer control and more intuitive task completion. Building on our previous work with the mouth-and-tongue interface, this paper integrates a mixed reality (MR) device to form an interactive system that enables shared control of the SRL. The system allows users to dynamically switch between voluntary and autonomous control, providing both flexibility and efficiency. A random forest model classifies 14 distinct tongue and mouth operations, mapping them to six-degree-of-freedom SRL control. In comparative experiments involving ten healthy subjects performing assembly tasks under three control modes (shared control, autonomous control, and voluntary control), shared control demonstrates a balance between machine autonomy and human input. While autonomous control offers higher task efficiency, shared control achieves greater task success rates and improves user experience by combining the advantages of both autonomous operation and voluntary control. This study validates the feasibility of shared control and highlights its advantages in providing flexible switching between autonomy and user intervention, offering new insights into SRL control.