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This paper presents design principles for comfort-centered wearable robots and their application in a lightweight and backdrivable knee exoskeleton. The mitigation of discomfort is treated as mechanical design and control issues and three…
This work presents a wearable human activity recognition (HAR) system that performs real-time inference directly inside a shank-mounted inertial measurement unit (IMU) to support low-latency control of a lower-limb exoskeleton. Unlike…
Gait phase estimation based on inertial measurement unit (IMU) signals facilitates precise adaptation of exoskeletons to individual gait variations. However, challenges remain in achieving high accuracy and robustness, particularly during…
Accurate prediction of human movements is required to enhance the efficiency of physical human-robot interaction. Behavioral differences across various users are crucial factors that limit the prediction of human motion. Although recent…
Wearable robotics for lower-limb assistance have become a pivotal area of research, aiming to enhance mobility for individuals with physical impairments or augment the performance of able-bodied users. Accurate and adaptive control systems…
For leg exoskeletons to operate effectively in real-world environments, they must be able to perceive and understand the terrain around them. However, unlike other legged robots, exoskeletons face specific constraints on where depth sensors…
Scaling dexterous robot learning is constrained by the difficulty of collecting high-quality demonstrations across diverse operators. Existing wearable interfaces often trade comfort and cross-user adaptability for kinematic fidelity, while…
Recent research has examined the possibility of using robots to guide evacuees to safe exits during emergencies. Yet, there are many factors that can impact a person's decision to follow a robot. Being able to model how an evacuee follows…
This paper presents an insole FSR (Force Sensing Resistor) to dynamically detect weight variations in an exoskeleton system. The proposed methodology is intended for tasks of lifting and lowering heavy weights with an industrial exoskeleton…
Dynamic bipedal walking on discrete terrain, like stepping stones, is a challenging problem requiring feedback controllers to enforce safety-critical constraints. To enforce such constraints in real-world experiments, fast and accurate…
Optimizing lower-body exoskeleton walking gaits for user comfort requires understanding users' preferences over a high-dimensional gait parameter space. However, existing preference-based learning methods have only explored low-dimensional…
To control the lower-limb exoskeleton robot effectively, it is essential to accurately recognize user status and environmental conditions. Previous studies have typically addressed these recognition challenges through independent models for…
Human motion prediction and trajectory forecasting are essential in human motion analysis. Nowadays, sensors can be seamlessly integrated into clothing using cutting-edge electronic textile (e-textile) technology, allowing long-term…
Exoskeleton locomotion must be robust while being adaptive to different users with and without payloads. To address these challenges, this work introduces a data-driven predictive control (DDPC) framework to synthesize walking gaits for…
Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor…
This study proposes the realization of various virtual environments using a lower limb exoskeletal robot for futuristic gait rehabilitation. The proposed method allows the user to feel virtual gravity, buoyancy, and drag while actively…
Soft robots offer significant advantages in adaptability, safety, and dexterity compared to conventional rigid-body robots. However, it is challenging to equip soft robots with accurate proprioception and tactile sensing due to their high…
The use of wearable robots has been widely adopted in rehabilitation training for patients with hand motor impairments. However, the uniqueness of patients' muscle loss is often overlooked. Leveraging reinforcement learning and a…
Proximity perception is a technology that has the potential to play an essential role in the future of robotics. It can fulfill the promise of safe, robust, and autonomous systems in industry and everyday life, alongside humans, as well as…
Machine learning methods are increasingly applied to ergonomic risk assessment in manual material handling, particularly for estimating carried load from gait motion data collected from wearable sensors. However, existing approaches often…