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Human-Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist human workers in their tasks and improve their efficiency. However, the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC)-based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker.

Automation of the bin picking task with robots entails the key step of pose estimation, which identifies and locates objects so that the robot can pick and manipulate the object in an accurate and reliable way. This paper proposes a novel point pair feature-based descriptor named Boundary-to-Boundary-using-Tangent-Line (B2B-TL) to estimate the pose of industrial parts including some parts whose point clouds lack key details, for example, the point cloud of the ridges of a part. The proposed descriptor utilizes the 3D point cloud data and 2D image data of the scene simultaneously, and the 2D image data could compensate the missing key details of the point cloud. Based on the descriptor B2B-TL, Multiple Edge Appearance Models (MEAM), a method using multiple models to describe the target object, is proposed to increase the recognition rate and reduce the computation time. A novel pipeline of an online computation process is presented to take advantage of B2B-TL and MEAM. Our algorithm is evaluated against synthetic and real scenes and implemented in a bin picking system. The experimental results show that our method is sufficiently accurate for a robot to grasp industrial parts and is fast enough to be used in a real factory environment.

Reported in our previous study on passive cycling support, the energy cost of knee extension can be reduced using the energy stored from knee flexion by torsion spring. In the current study, the planar spiral spring is applied to attain the compact design of the cycling augmented knee exoskeleton (CAKE-2). The surface electromyography (EMG) results over the rectus femoris muscles of three healthy male participants performing constant power cycling on a trainer at 200 W and 225 W are analyzed in time-frequency via the continuous wavelet transform. In all cycling tests with and without the exoskeletons worn on both legs, no sign of peripheral muscle fatigue or significant change in the EMG median power spectral frequency (MDF) appears throughout the two-minute cycling trials. At the same cycling speed and leg cadence, the average of EMG-MDF increases with the exercise intensity. At the same cycling power, less quadriceps activity can be observed from all the participants when the spring support was used during cycling. The capability to modify the unbalanced effort required from the quadriceps and the hamstring during cycling without requiring an external energy source is applicable for cycling enhancement and rehabilitation applications.

Purpose: Photoreceptor degeneration is a major cause of visual loss in various retinal diseases, including retinal detachment (RD) and neovascular AMD, but the underlying mechanisms remain elusive. In this study, the role of TNFα in RD-induced photoreceptor degeneration was investigated., Methods: RD was induced by subretinal injection of hyaluronic acid. Photoreceptor degeneration was assessed by counting the number of apoptotic cells with TdT-dUTP terminal nick-end labeling (TUNEL) 3 days after RD and measurement of the outer nuclear layer (ONL) thickness 7 days after RD. As the target of anti-inflammatory treatment, the expression of TNFα, with or without dexamethasone (DEX) was examined in rats by real-time PCR. To understand the role of TNFα in photoreceptor degeneration, RD was induced in mice deficient in TNFα or its receptors (TNFR1, TNFR2, and TNFR1 and -2), or in wild-type (WT) mice by using a functionally blocking antibody to TNFα. CD11b(+) cells in the outer plexiform layer (OPL) and subretinal space were counted by immunohistochemistry (IHC)., Results: Treatment with DEX (P = 0.001) significantly suppressed RD-induced photoreceptor degeneration and the expression of TNFα. RD-induced photoreceptor degeneration was significantly suppressed with specific blockade of TNFα (P = 0.032), in mice deficient for TNFα (P < 0.001), TNFR2 (P = 0.001), or TNFR1 and -2 (P < 0.001). However, lack of TNFR1 did not protect against RD-induced photoreceptor degeneration (P = 0.060). Müller cell activation was unchanged in WT and TNFα(-/-) mice. Recruitment of CD11b(+) monocytes was significantly lower in the TNFα(-/-) mice compared to WT mice (P = 0.002)., Conclusions: TNFα plays a critical role in RD-induced photoreceptor degeneration. This pathway may become an important target in the prevention of RD-induced photoreceptor degeneration.

Positions of substitution with sulphate in three water-soluble sulphated derivatives of chitosan were analysed by 13C n.m.r. The structures of N-acetylchitosan 3,6-O-disulphate, sodium chitosan N-, 6-O-disulphate, and sodium chitosan 6-O-monosulphate were confirmed.