Communications in Information and Systems

Starting from the vector multipliers, the inner product, norm, distance, as well as addition of two vectors of different dimensions are proposed, which makes the spaces into a topological vector space, called the Euclidean space of different dimension (ESDD). An equivalence is obtained via distance. As a quotient space of ESDDs w.r.t. equivalence, the dimension-free Euclidean spaces (DFESs) and dimension-free manifolds (DFMs) are obtained, which have bundled vector spaces as its tangent space at each point. Using the natural projection from a ESDD to a DFES, a fiber bundle structure is obtained, which has ESDD as its total space and DFES as its base space. Classical objects in differential geometry, such as smooth functions, (co-)vector fields, tensor fields, etc., have been extended to the case of DFMs with the help of projections among different dimensional Euclidean spaces. Then the dimension-varying dynamic systems (DVDSs) and dimensionvarying control systems (DVCSs) are presented, which have DFM as their state space. The realization, which is a lifting of DVDSs or DVCSs from DFMs into ESDDs, and the projection of DVDSs or DVCSs from ESDDs onto DFMs are investigated.

Place recognition plays an essential role in the field of autonomous driving and robot navigation. Point cloud based methods mainly focus on extracting global descriptors from local features of point clouds. Despite having achieved promising results, existing solutions neglect the following aspects, which may cause performance degradation: (1) huge size difference between objects in outdoor scenes; (2) moving objects that are unrelated to place recognition; (3) long-range contextual information. We illustrate that the above aspects bring challenges to extracting discriminative global descriptors. To mitigate these problems, we propose a novel method named TransLoc3D, utilizing adaptive receptive fields with a pointwise reweighting scheme to handle objects of different sizes while suppressing noises, and an external transformer to capture longrange feature dependencies. As opposed to existing architectures which adopt fixed and limited receptive fields, our method benefits from size-adaptive receptive fields as well as global contextual information, and outperforms current state-of-the-arts with significant improvements on popular datasets.

Silhouette extraction of foreground objects appears frequently in various real-world applications, such as Advanced Driving Assistant System, Intelligent Monitoring System, and movie production. Plenty of solutions have been developed to extract silhouette in RGB image with only color information. Since those color based silhouette extraction methods still have difficulties to separate overlapping foreground objects and eliminate excessive segmentation, this paper proposes a novel object segmentation method using color and depth information in RGB-D images. Firstly, we remove the ground plane using the normal map of depth image. Secondly, to separate foreground objects at different distances completely and correctly, the deep Residual Network (ResNets) and Otsu’s multithresholding method are combined to divide the depth image into multiple layers. Each depth layer contains only one foreground object or objects at same distance. Finally, the outline of foreground object is extracted directly from its depth layer, and refined with color information. Experimental results demonstrate that our method has a better performance than those using color or depth information only, and extracts more types of objects than neural networks.

The complex underwater environment causes light to suffer from scattering effects and wavelength-dependent attenuation, and underwater images exhibit color deviation and low contrast, which hinder the progress of related underwater tasks. Deep learning algorithms now make extensive use of multi-scale features to improve underwater image quality, but the majority of these methods do not take channel differences into account while propagating features. To this end, we propose a cross aggregation transformer (CAT), which utilizes three stages of projection-crossing aggregation to adaptively select beneficial channels. This paper also designs a dynamic supplement underwater image enhancement network, which consists of a shallow network and an enhancement network. Through the encoder/decoder structure, the enhancement network restores the original appearance of the underwater image, while the shallow network extracts the shallow features at different scales. Both networks are designed to focus on under-enhanced regions and supplementary details in real time through the residual supplement module (RSM). The experimental findings demonstrate that CAT and RSM efficiently improve network performance and elevate the network above other advanced methods on various datasets.

In this paper, an “active-caster” omnidirectional wheel mechanism is introduced. The original type of the active caster was invented more than twenty-five years ago, and various types of active casters were developed by the author’s group, some of which are described in this paper as well. Unlike other omnidirectional wheels such as Mecanum Wheel or Universal Wheel, active casters do not need freely rotating parts. An active caster is an orientable wheel with a normal tire, the steering and wheel shafts of which do not intersect like a normal passive caster. The wheel and steering shafts are driven by the respective motors to perform the omnidirectional movement of the robot.

A lower-limb power-assist exoskeleton robot is a wearable device that assists persons in their daily activities. Although the main purpose of the lower-limb exoskeleton robot is to assist the intended motion of the user, the stability of the robot’s posture is still one of the biggest challenges. This paper focuses on the balance aspect of the exoskeleton robot in terms of control considering Zero Moment Point (ZMP) that is widely used in biped robots. A ZMP based fall prevention assist method, that prevents the user from falling down by giving equivalent external motion modification force to the user during dynamic walking on even terrains, is proposed in this paper. Fall prevention assist strategy is changed between a double support phase and a single support phase in the proposed method. Position of swing leg, velocity of swing leg, and change rate of ZMP are considered as an index to stabilize the posture of the exoskeleton during dynamic walking in the proposed method. In the proposed method, fuzzy control approach is applied to keep the ZMP inside the support polygon by generating the equivalent motion modification force at the chest or back of the user by the lower-limb exoskeleton for fall prevention assist during walking without making additional steps. The effectiveness of the proposed method is evaluated through experiments.

There is a surgical method called Interventional Radiology (IR) in which needles and catheters are inserted into the body using image diagnostic techniques such as CT fluoroscopy and X‑ray fluoroscopy images to perform percutaneous treatment. IR has been applied to various treatments including lung cancer treatment, liver cancer treatment, and biopsy. Since it is less invasive than conventional surgery, it is possible to leave the hospital within 3 to 4 days after surgery. Therefore, IR surgery has been receiving increasing attention in recent years. Doctors are, however, exposed to strong radiation in the case of under CT guidance. In order to overcome this problem, we developed remote-controlled IR assistance robot named as Zerobot. And in order to make the operation succeed regardless of the difference of techniques of doctors, we have studied an automated puncture system with the robot. During the automated motion, the collision of the robot with CT gantry should be avoided. In this report, a method to detect contact between Zerobot and CT gantry is proposed.

Evaluation of oocytes and embryos is an important technique for many biomedical applications. In this study, we proposed a method to measure individual oocytes’ oxygen consumption rate by fluorescence oxygen measurement using a fluorescent oxygen sensor arranged in a striped pattern on a microchamber. For oxygen concentration measurement, a fluorescent oxygen microsensor array was prepared using a hydrophilic photo-crosslinkable resin and fluorescent oxygen indicator. The sensor was fabricated by forming a stripe pattern on polydimethylsiloxane using photopolymerization and molding methods. Since the oxygen permeabilities of polydimethylsiloxane and the medium are similar, the oxygen concentration distribution around the oocyte follows the spherical diffusion theory. The sensor array was used to detect the distribution of oxygen concentration in two-dimensional plane. The oxygen consumption rate of the single oocyte was obtained by image analysis and Fick’s law. A single mouse oocyte’s oxygen consumption rate on the microchamber could be measured without contact of sensor probe to the target oocyte within $8$ seconds ($0.59 \pm 0.03 \: \textrm{fmol/s})$.

Various kinds of human-friendly robot partners have recently been developed to provide humans with superior services. Manipulation skills, including grasping, arranging, and delivering, are essential for home applications. A robot partner is designed to grasp the meaning of human behavior and their intention in shared spaces to assist older people at home. As a result, the robot partner requires the cognitive ability to comprehend states of the environment based on both people’s and robot partners’ physical and sensory embodiment. This research presents a human-robot interaction technique for handover behaviors based on cognitive contexts. First, we describe how to share a person’s cognitive environment with a robot companion using the relevance idea presented in Cognitive Pragmatics. The perceived cognitive environment of humans contains a type of spatial topological structure, such as relative placement and proximity among objects. Furthermore, the human cognitive environment is continually updated due to the cyclic process of perception and action. As a result, we will look at how to apply topological mapping approaches in cognitive contexts. Next, using the idea of the perceiving-acting cycle presented in Ecological Psychology, we apply topological mapping methods of Growing Cell Structure (GCS) and Growing Neural Gas (GNG). The GCS represents the effectivity in the action system. In contrast, the GNG represents the human and robot task space. The experimental findings and real-world robot application examples indicate that the robot can correctly estimate human intention and conduct handover actions. Finally, we examine the effectiveness of the proposed approach and future research directions in the human-robot interaction based on the perceiving-acting cycle.

The circadian genes in mammals are involved in a transcriptiontranslation feedback loop, whereas in cyanobacteria, there exists a post-translational oscillator (PTO) consisting of KaiA, KaiB, and KaiC. KaiC has both ATPase and kinase activities. ATP binding, hydrolysis and phosphate transfer drive the dynamics of circadian system. In this study, we built a mathematical model for our latest found circadian genes Ruvbl1/2 (Ruvbls) and added the model to a previously published model for mammalian circadian system. RUVBLs are the first ATPase known to directly participate in the mammalian circadian system. We described the entire process whereby an ATPase is involved in the traditional transcriptiontranslation feedback loop. Additionally, a phase-shift adenosinelike molecule, cordycepin, which was discovered from our highthroughput screening and targeted RUVBLs, was also simulated in our mathematical model. Notably, this model gives a more detailed description of circadian system, and considers the participation of ATPase for the first time, which can lead to a deeper insight into mammalian circadian clock regulation. Our model aligns well our experimental data. Further, based on wet-lab experiments and drylab modeling, we discussed the role of ATP and ATPase in mammalian circadian system. Finally, we compared the similarities and differences between KaiC and RUVBLs, and discussed the potential of RUVBLs as a component of mammalian post-translational oscillator.