This study proposes a method for correcting trajectory data of a robot using iterative learning to mimic the motion of a human with a comparable force level. Currently, trajectory generation using direct teaching is often used to teach robots more flexible movements. Although such a teaching method can produce ideal trajectories, it may neglect the reproducibility of the force. Therefore, we propose a method that can reproduce the originally required sense of force by correcting the original trajectory data using iterative learning. Moreover, the reduction in the force error using our method is verified.

Lunar Terahertz Surveyor for Kilometer-scale Mapping (TSUKIMI), a collaborative mission for lunar exploration, is introduced. We numerically explore terahertz scattering and emission from the lunar surface as an initial step forward. Regarding the characterization of the lunar surface, the power-law spectrum is adopted to model the roughness. While for the dielectric constant of the lunar surface, tentatively simplifying into a homogeneous condition. The scattering and emission models are briefly described. To investigate the terahertz scattering effect from the lunar surface, we conducted the preliminary experiments with dielectric constant and surface roughness using THz- TDS and T-Ray 4000 Picometric, respectively. The measurement results are subsequently presented.

We present the expected performance for a ground-based terahertz (THz) radiometer, a plan to be launched on the TERahertz EXplore-1 (TEREX-1) Mars exploration microspacecraft. The small THz passive radiometer has been developed for the TEREX series of future microspacecrafts. This spacecraft is an opportunity for organizations with limited resources and technology to conduct frequent missions to Mars well suited for resource exploration in contrast to all of the current and past Mars missions of large/giant class missions with fully government lead. The observation frequencies of the TEREX-1 radiometer are 474.64–475.64 and 486.64–487.64 GHz with a 100-kHz resolution, and the double-sideband noise temperature less than 3000 K. A theoretical error analysis is performed with the instrument characteristics to assess for the first time up-looking observations of atmospheric oxygen molecules (O2) and water vapor (H2O). Measurement errors for O2and H2O are 7%–22% and 14%–25% with 8–17- and 5–10-km vertical resolution in the vertical ranges 0–55 and 0–25 km, respectively. TEREX-1 is also capable to measure minor species, O3and H2O2, with a precision better than 30% within two independent layers. We used the integration time of 1 h for all simulations. Our theoretical simulation showed the instrument characteristics of the TEREX-1 sensor are able to observe vertical profiles of O2and H2O abundances with the same level of the large class missions.

In order to construct a comfortable communication in the VR space, it is important to improve the speech comprehension in environmental noise. Although there have been many reports on the interaction between vision and acoustic, few studies using noisy VR spaces. In this study, sixteen Japanese male and female were tested to listen to a some sentence in a VR space with environmental noise, to evaluate the effect of the visual stimulus to the avatar speech comprehension against the environmental noise, with using the up-and-down method. The results showed that the cocktail party effect was also observed in the VR avatars, and the cocktail party effect continued even if the avatar vanished visually. In addition, it was suggested that the cocktail party effect was enhanced if the lip of the avatar synchronized correctly.

In order to pick bolts stacked in bulk using a robot, it is necessary to obtain the most suitable grasping position. Recently, deep learning-based methods have been proposed. However, learning takes a long time and much effort to prepare the training. In order to avoid this, this research proposes a template matching-based method. First of all, we defined some states where the bolt can be grasped stably. By efficiently searching the grasping position where the objective function is maximized using differential evolution (DE), the proposed method can acquire the grasping position in two seconds. After an original gripper was made using a 3D printer and attached to the robot, we experimented using 60 bolts (M6-20). The results show 86% of the success rate.

This paper analyzes grasp stability of two objects in two dimensions. In the previous researches on the grasp stability, the number of grasped objects is restricted to 1. For efficiency of tasks, multiple objects had better been grasped and manipulated by a robot hand. In order to design stable grasp, grasp stability of multiple objects must be quantitatively evaluated. In case of two grasped objects in two dimensions, the number of parameters of object displacement is 6. However, the displacement of the objects is constrained by each other, because the contact between the objects must be maintained. Independent parameters of the object displacement are provided and then finger displacement is derived. The grasp stability is evaluated from the viewpoint of the potential energy method. From numerical examples, the effect of curvature at contact point between two objects is demonstrated. The effect of this curvature stands for the feature of multiple objects.

This paper proposes an algorithm for identification of contact conditions between a grasped object and external environment from position and velocity information of a robot hand. The contact conditions mean contact type, contact position, and contact force. Soft finger contact type, line contact type, and plane contact type are considered in addition to point contact type. The contact type is identified by rank of the matrix that places estimated angular velocity of the object at contact point. Contact position, contact normal and contact line are also estimated. This method has the following merits as compared with the method using 6-axes force information described in the previous paper. The identification problem is reduced to the problem of solving linear equations. The required number of active sensing motion is less.

This paper discusses a method for identification of contact conditions from the information of 6-axes force sensor equipped with a robot hand. The previous paper (1999) has the following problems: the noise of sensing force was not considered, and hence the estimates obtained by the previous method are biased from true value, and the identification of contact types depends on an unknown contact position. In this paper we consider the noise of force. We propose a method of removing the bias from the estimates. Hence, it is guaranteed that asymptotically unbiased estimates are obtained. The contact types can be judged by eigenvalues of a covariance matrix, which is derived from estimates of the contact moment. The effectiveness of the algorithm is demonstrated by simulations.

We discuss stability of 3D grasps by using a three-dimensional spring model (3D spring model). Many works have described stability of a frictionless grasp. These works used a one-dimensional spring model (1D spring model) for representation of frictionless contact as a matter of course. However, a 1D spring model involves the following problems: (i) displacement of a finger is restricted to one dimension along the initial normal at contact point; and (ii) it is not clearly considered that a finger generates contact force to the object along the normal direction only. To overcome the problems and provide accurate grasp stability, we introduce a 3D spring model. Then a finger's displacement is relaxed and a finger's contact force is precisely formulated. We analyze grasp stability from the viewpoint of the potential energy method. From numerical examples, we show that there exists an optimum contact force for stable grasp. Moreover, we also analyze a frictional grasp by using contact kinematics of pure rolling. By comparing frictional grasp stability with a frictionless one, we prove that friction enhances stability of a grasp.

When a grasped object is in contact with external environment, it is required to identify contact conditions prior to performing the assembly tasks. This paper discusses a method for identification of contact conditions from the information of force sensor equipped with the robot hand. This paper treats the practical case where sensing data are contaminated with noise. We propose an efficient and analytical algorithm for identifying contact conditions by using an active force sensing method. The algorithm can identify not only contact position and contact force, but also contact type such as soft finger contact type, line contact type, and plane contact type. These contact types are characterized by a standard deviation of contact moments. The contact position is estimated by a least-squares method. The contact moment is then estimated from noisy observations and its eigenvalues are analyzed. The contact type can be judged by the eigenvalues of estimated contact moment. The effectiveness of the algorithm is demonstrated by simulations.

Proposes a method for analyzing the stability of grasps. The characteristic points in this paper are to consider the curvature of both hand and object at contact points and the grasp with friction and frictionless contact. From this analysis, it is shown that the grasp using round fingers is more stable than using sharp fingers. Moreover, we establish the condition on the finger's stiffness to stabilize the grasp with friction. It is proved that the required stiffness of fingers are decreased by considering the curvature. The stability analysis is greatly simplified by using potential energy of the grasp system and is of practical use.