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In this paper, we have dealt with the problem to transport large heavy objects using a group of small mobile robots. Generally, payload of the robot, the maximum weight of the object that the robot can operate, is very small and they cannot transport heavy objects with standard coordinated grasping methodology. This paper considers a method of transporting an object using handcarts by tilting the object to load it on the handcarts. To resolve the problem of avoiding overturning of the object by the robots and sliding of the handcart while tilting the object, an outrigger device is used to prevent the first problem of tilting, and a handcart locking device is used to prevent the second problem of sliding. As both devices need to be used only when necessary, a mechanism that can fix and release the devices according to situations is newly designed. Two robots were trial fabricated: an object-tilting robot equipped with an outrigger mechanism and a handcart transport robot to handle the handcarts. Both robots are smaller than 0.6 m × 0.6 m with payload of 2.5 kg. They are equipped with a handcart mechanism that can be locked and unlocked. The use of the coordination and lock mechanisms by these robots has realized transport of objects approximately 1 m high and weighing approximately 35 kg and demonstrated the effectiveness of the proposed system in a real-world environment where robot mechanism errors, mobility errors, and observation errors occur.

The human body is a complex system driven by hundreds of muscles, and its control mechanisms are not sufficiently understood. To understand the mechanisms of human postural control, neural controller models have been proposed by different research groups, including our feed-forward and feedback control model. However, these models have been evaluated under forward and backward perturbations, at most. Because a human body experiences perturbations from many different directions in daily life, neural controller models should be evaluated in response to multidirectional perturbations, including in the forward/backward, lateral, and diagonal directions. The objective of this study was to investigate the validity of an NC model with FF and FB control under multidirectional perturbations. We developed a musculoskeletal model with 70 muscles and 15 degrees of freedom of joints, positioned it in a standing posture by using the neural controller model, and translated its support surface in multiple directions as perturbations. We successfully determined the parameters of the neural controller model required to maintain the stance of the musculoskeletal model for each perturbation direction. The trends in muscle response magnitudes and the magnitude of passive ankle stiffness were consistent with the results of experimental studies. We conclude that the neural controller model can adapt to multidirectional perturbations by generating suitable muscle activations. We anticipate that the neural controller model could be applied to the study of the control mechanisms of patients with torso tilt and diagnosis of the change in control mechanisms from patients’ behaviors.

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Post-stroke complications are the second most frequent cause of death and the third leading cause of disability worldwide. The motor function of post-stroke patients is often assessed by measuring the postural sway in the patients during quiet standing, based on sway measures, such as sway area and velocity, which are obtained from temporal variations of the center of pressure. However, such approaches to establish a relationship between the sway measures and patients' demographic factors have hardly been successful (e.g., days after onset). This study instead evaluates the postural sway features of post-stroke patients using the clustering method of machine learning. First, we collected the stroke patients' multi-variable motion-capture standing-posture data and processed them into t s long data slots. Then, we clustered the t-s data slots into K cluster groups using the dynamic-time-warping partition-around-medoid (DTW-PAM) method. The DTW measures the similarity between two temporal sequences that may vary in speed, whereas PAM identifies the centroids for the DTW clustering method. Finally, we used a post-hoc test and found that the sway amplitudes of markers in the shoulder, hip, knee, and center-of-mass are more important than their sway frequencies. We separately plotted the marker amplitudes and frequencies in the medial-lateral direction during a 5-s data slot and found that the post-stroke patients' postural sway frequency lay within the bandwidth of 0.5–1.5 Hz. Additionally, with an increase in the onset days, the cluster index of cerebral hemorrhage patients gradually transits in a four-cluster solution. However, the cerebral infarction patients did not exhibit such pronounced transitions over time. Moreover, we found that the postural-sway amplitude increased in clusters 1, 3, and 4. However, the amplitude of cluster 2 did not follow this pattern, owing to age effects related to the postural sway changes with age. A rehabilitation doctor can utilize these findings as guidelines to direct the post-stroke patient training.

Atomic force microscopy has enabled imaging at the sub-molecular level, and 3D mapping of the tip-surface potential field. However, fast identification of the surface still remains a challenging topic for the microscope to enjoy widespread use as a tool with chemical contrast. In this paper, as a step towards implementation of such function, we introduce a control scheme and mathematical treatment of the acquired data that enable retrieval of essential information characterizing this potential field, leading to fast acquisition of images with chemical contrast. The control scheme is based on the tip sample distance modulation at an angular frequency ω, and null-control of the ω component of the measured self-excitation frequency of the oscillator. It is demonstrated that this control is robust, and that effective Morse Parameters that give satisfactory curve fit to the measured frequency shift can be calculated at rates comparable to the scan. Atomic features with similar topography were distinguished by differences in these parameters. The decay length parameter was resolved with a resolution of 10 pm. The method was demonstrated on quenched silicon at a scan rate comparable to conventional imaging.