The necessity of the soft gripping devices is increasing day-by-day in medical robotics especially when safe, gentle motions and soft touch are necessary. In this paper, a novel asymmetric bellow flexible pneumatic actuator (AFPA) has been designed and fabricated to construct a miniaturised soft gripper that could be used to grip small objects. The model of AFPA is designed using solid works and its bending motion is simulated in Abaqus software for optimisation and compared with experimental results. The actuator is fabricated using compression molding process that includes micromachining of the molds. Experiments conducted show the bending characteristics of the actuator at different pressures. The actuator shows excellent bending performance and the eccentricity in its design supports increased bending or curling motion up to a certain extent compared to normal bellows without eccentricity. The effects of profile shape and eccentricity on the actuator performance are analysed and the results are presented.

Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over $93\%$.

Monitoring patients using vision cameras can cause privacy intrusion problems. In this paper, we propose a patient position monitoring system based on a patient cloth with unobtrusive sensors. We use flexible sensors based on polyvinylidene fluoride, which is a flexible piezoelectric material. Theflexiblesensorsareinsertedintopartsclosetothekneeandhipoftheloosepatientcloth. We measure electrical signals from the sensors caused by the piezoelectric effect when the knee and hip in the cloth are bent. The measured sensor outputs are transferred to a computer via Bluetooth. We use a custom-made program to detect the position of the patient through a rule-based algorithm and the sensor outputs. The detectable postures are based on six human motions in and around a bed. The proposed system can detect the patient positions with a success rate over 88 percent for three patients.

This paper focuses on real-time walking pattern generation for humanoid robots with linear inverted pendulum model (LIPM). In general, there are many issues in generating proper walking patterns of center of mass and zero moment point (ZMP) with the LIPM since the LIPM has two drawbacks such as instability and non-minimum phase property. For resolving these difficulties, the paper proposes a new real-time approach by combining a feedback and a feedforward controller. The feedback controller employs a pole placement method which shifts the poles of the LIPM in order to improve system stability. The feedforward controller utilizes advanced pole-zero cancelation by series approximation method (APZCSA) for reducing non-minimum phase property which occurs by an unstable zero and is not able to be dealt with by the feedback controller. In addition, the APZCSA improves the tracking error induced by finite series approximation. Using the two controllers, the proposed method makes the transfer function of overall walking pattern generation system approximately unity and consequently generates a stable walking pattern which follows a desired ZMP according to walking path. The efficiency of the proposed method is verified by walking pattern planning examples and experiments with the humanoid robot MAHRU-R.

This letter presents a distance-based formation control with the goal assignment for multiple nonholonomic mobile robots. One of the most challenging issues in the distance-based formation control is the convergence to undesirable formations caused by the gradient-based control law. Even though the target formation is globally rigid, only the local stability is guaranteed. In order to overcome this restriction, we present a novel goal assignment algorithm switching the goal positions of two agents in the target formation. This assignment algorithm helps to avoid the convergence to undesirable formations and thus the global asymptotic convergence can be achieved. To show the effectiveness of the proposed distance-based formation controller with the goal assignment algorithm, simulation and experimental results are provided.