In recent times, aerial robots have gained prominence in critical applications such as natural disaster response and social security. However, existing control interfaces like joysticks and touch screens often pose significant challenges for untrained users, particularly in complex tasks and remote operations. This study introduces an innovative, novice-friendly drone control system, leveraging the familiar framework of a conventional car steering system combined with a VR headset for visual feedback. This design aims to provide an immersive, carlike experience to users unfamiliar with UAV operation. The core objective is to bridge the knowledge gap for inexperienced users, enabling them to effectively control drones in critical scenarios. To evaluate the system’s efficiency and user experience enhancement, we devised an indoor search-and-rescue experiment simulating an earthquake disaster scenario. The study includes a comparative analysis between traditional joystick control and our car steering-based system. Additionally, we will conduct a comprehensive user study to assess the improvement in user experience offered by our interface. This research contributes to making drone technology more accessible and effective for general users, particularly in high-stakes environments.

Cable-driven serial robots have gained significant growth because of their compact size and low inertia characteristics. However, one major problem of cable-driven serial robots is motion coupling issue that one joint motion will cause movement of the other joints, resulting in a complicated control. In this paper, we proposed a novel method to decouple the joint motion by using a noncircular pulley. The length change of driving cables on a joint pulley due to the coupling issue is compensated by the noncircular pulley. The calculation process of the pulley profile, the mechanical design of the decoupling system, and control system of the cable-driven robot prototype are introduced. Experiments have been conducted to evaluate the performance of the motion decoupling method. The results demonstrate that the noncircular pulley can solve the motion coupling issue by keeping the cable length nearly constant with small errors.

Musculoskeletal disorders (MSDs) are pervasive in the workforce and constitute the single largest category of work-related illness. The root cause for MSDs is complex. However, there is little dispute that MSD morbidity is primarily due to physical and psychosocial risk factors, and these two domains of risk factors share a common upstream determinant. A work organization influences both the physical load patterns and psychosocial features. In this paper, we propose a technology-facilitated intervention program that could lead to an improved safety culture in workplaces. The program is aimed at addressing one of the physical risk factors, i.e., rest breaks, and a psychosocial risk factor, i.e., social support. First, a wearable soft orthosis is used to detect the types of physical activities and load patterns, and to derive an intelligent rest break schedule for each type of activity and load patterns. The orthosis would also remind the participant to take a rest break at appropriate times. Second, a mobile app is developed to cultivate a learning community where the participants could seek and provide social support and increase their awareness of occupational safety. We collected some preliminary app usage data and developed a methodology of identifying app usage patterns using both supervised and unsupervised learning. The feasibility of the method is validated using synthesized data derived from the collected data.

Work-related musculoskeletal disorders are generated, preceded, or aggravated by repeated or continuous use of certain parts of the body. Orthoses have been developed to help people prevent or treat these kinds of disorders. In this paper, we developed a novel flexible orthosis based on bend sensors to count the times of the repetitive movements and remind the worker to take adequate rest after a period of repetitive movements, thus, to reduce the possibility of developing musculoskeletal disorders. A novel movement detection method is developed to count the times of the repeating movement by using the trends/slopes of the rotation angles. Experiments have been conducted to evaluate the accuracy of the novel movement detection method. The results demonstrate that the movement detection method can accurately count the times of the wrist movement with varying rotation angles and speed and issue reminders for rest.

Due to the degeneration of musculoskeletal structure and strength, the elderly population is facing significant mobility challenges. Walkers are widely used for mobility-impaired people. In this research, a smart walker has been developed by using a hybrid motion model (HMM) and a machine learning model based on the vertical interaction force to match the velocity between the walker and its user, which can reduce the horizontal interaction force thus to help lower the operational effort. It is equipped with only force sensors on the handlebars as a human-robot interface. The human motion is modeled by using the HMM in which an inverted pendulum model is used in the single support phase and a constant velocity model is used in the double support phase. A novel gait phase detector is built based on a machine learning method to correlate the force information and the walking gait phases. Experiments with three subjects are carried out to verify the effectiveness of the gait phase detection method and the hybrid motion model. The results demonstrate that the walker can accurately identify gait phases with more than 90 % accuracy and the horizontal interaction force is reduced to around 50 % of that under the constant velocity model and power-off condition when using the HMM during walking.

Robots for surgery and rehabilitation have emerged and are gaining popularity among patients and medical doctors with their obvious benefits, such as overcoming obstacles from human users’ physical restraints, reducing physicians’ workload, and enhancing the efficacy of medical treatment. The development of medical robots meets two challenges related to their special application environments, including sterilization hazards and size/weight limitation. Medical robots (e.g., surgical robots) usually need to have close contact with human skin or organs, which need to be sterilized. However, chemical or heat sterilization on the robots poses an inevitable risk of damage on the motors, sensors, and other electronic components. The size of the surgical robot needs to be compact to gain access to surgical sites. The rehabilitation robots that patients wear have to limit their size and weight. Wire-driven actuation is a potential solution to solve these issues by avoiding the use of bulky mechanical gears and links and locating the electronic components far away from the sterilization environment. This paper presents the development of a novel wire-driven universal joint for medical robot design. With its special structure, this robotic joint has self-decoupled kinematics which can simplify its control system and increase motion accuracy. Benchtop experiments are conducted to verify the functionality of this joint and the effectiveness of its self-decoupled kinematics.

Gastroesophageal reflux disease (GERD) is a common digestive disorder that usually has symptoms including reflux, heartburn, pain when swallowing, etc. Evolving from traditional needle acupuncture and electroacupuncture (EA), transcutaneous electrical acustimulation (TEA) becomes a popular method for treating GERD with its non-invasive intervention feature. Recently, an even more effective method synchronized with respiration in TEA is emerging. However, the current procedure for conducting synchronized TEA (STEA) treatment is mostly based on patients’ manual synchronization, which can generate a big delay or error in the synchronization, significantly compromising the effectiveness of this method. To solve this issue, this research presents a novel STEA device that can automatically detect the user’s respiration wave and synchronize with the breath to conduct TEA. With this automated synchronization device, the patients can inhale and exhale with an uninterrupted and normal respiration pace while receiving the TEA treatment, largely simplifying the treatment procedures and enhancing the effectiveness of the method. The system of the STEA device consists of a chest strip respiration sensing element, a stimulation point identifier, and a stimulation current generator. Experiments were conducted to verify human respiration detection, electrical current generation and synchronization. The results demonstrated the feasibility, effectiveness and reliability of the automated device system.

Unmanned Aerial Vehicles (UAVs), often referred as drones, have been widely implemented for civilian, commercial, search and rescue, and military operations with the advantages of easy deployment, low cost, automation, as well as, most importantly, allowing the execution of dangerous or difficult tasks remotely and safely. However, current UAVs are equipped with a skid or wheel landing gear that limits the application of UAVs to an even and flat ground for safe landing and taking off; this constraint impedes the development of UAVs for application in extreme environments, such as war fields and remote wilderness where proximate level ground is inaccessible. The ability of UAVs to land on un-level ground would help broaden the application of UAVs; in particular, the ability to go beyond thermal imaging to locate a lost hiker with the ability to land and deliver life-sustaining resources in a more timely manner offers a benefit to human rescue missions. This paper presents an innovative robotic landing system consisting of three slanted legs, each individually controlled by a motor. The footpad of each leg has an integrated force sensor for detecting ground touch. An inclinometer is installed on the platform of the landing system to sense the UAVs orientation during landing. Thus, the landing system can keep the platform horizontal when it lands on the ground by extending or retracting the legs. The feasibility and effectiveness of the robotic method have been demonstrated by several indoor and outdoor experiments.

Single Incision Laparoscopic Surgery (SILS) is a fast-growing method in the field of MIS (Minimally Invasive Surgery) that has the potential to represent the future of laparoscopic surgeries. The major benefits of SILS results from a single incision which makes surgeries essentially scar-less, and it can reduce wound infection substantially as well as recuperation time. Many new researches are now focusing on developing cutting edge technologies to support SILS; however, the practical applications of SILS are constrained by a number of intricacies such as space limitation, absence of dexterous multitasking tools, lack of sufficient actuation force and poor visualization. Deployment and retraction of surgical tools or robots are done manually in the absence of a multitasking tool manipulator which increases the surgery time, risk of injury and surgeon’s fatigue. Our research focuses on designing a novel operative hardware (multitasking manipulator) to facilitate the SILS technique with automatic tool changing capability. A wire driven mechanism has been implemented in the design to minimize the damage to the electronic hardware during sterilization since the electronic actuation and sensing components are located remotely from the end-effector which requires heat or chemical sterilization before surgery. And a wire-driven articulated robotic arm has also been designed to support the manipulator. The details of the robotic design and analysis are conducted in the paper. The feasibility of this robotic method has been demonstrated by experiments.