This paper presents a nonprehensile manipulation using an underactuated mechanism, in which three degrees of freedom (DoF) of a planar object are controlled on a vibrating plate driven by only one actuator. First, the model of a manipulator with a plate end effector is proposed. The manipulator employs an underactuated mechanism including an active joint and multiple passive viscoelastic joints, in which the joint axes are arranged nonparallel to each other. Based on the model, the orbit of the plate for a sinusoidal displacement input to the active joint is theoretically derived. It is revealed that the orbit becomes ellipse-like and the orbital direction has a potential to be switched according to the increase of the input frequency. Subsequently, the contribution of the switching of the orbital direction to the three-DoF manipulation of the object is explored via trajectory maps of point masses. Eight primitives utilizing the plate orbits in both counter-clockwise and clockwise directions are designed. Finally, the proposed method is demonstrated by experiments.
In this paper, we describe the development of a lower limb exoskeleton actuatorless mechanism to assist the standing motion of rehabilitation patients which we are developing. First, the standing movements were classified into three phases. Next, the development mechanism is explained, and the principle of support for the standing motion is described. Finally, the result of motion simulation using mechanism analysis software is described.
Humans can learn word meanings by associating objects with words even in an environment with a plurality of objects by using joint attention, which is an ability to detect a target object that others pay attention to. In this paper, we propose a method for robots to learn word meanings using joint attention and co-occurrence of objects and words, which is modeled by multimodal latent Dirichlet allocation (MLDA). A target object is detected by using MLDA and joint attention, and MLDA is updated by the detected object. This updated MLDA can improve the accuracy of the target object detection.
Humans can learn rules of interactions by observing others' interactions. To learn various interactions flexibly, we believe such an ability is also important for robots. To this end, we proposed Coupled Gaussian Process-Hidden Semi-Markov Models (C-GP-HSMM) that enabled robots to learn rules of interactions by observing motions of two persons. However, not only motions but also multimodal information is used in the actual human interactions. Therefore, in this paper, we extend C-GP-HSMM into a method to learn rules from multimodal data. In experiments, we show the proposed model can estimate the rules of a game, which contains multimodal interactions.
A robotic hand design suitable for dexterity should be examined through functional tests. To achieve this, we developed a mechanical glove, a rigid wearable glove which enables us to develop the corresponding isomorphic robotic hand and evaluate the hardware properties. After the development of the mechanical glove, the effectiveness of multiple degrees-of-freedom (DOF) was evaluated by human participants. Several fine motor skills were evaluated using the mechanical glove under two conditions: one-DOF condition and three-DOF condition. To our knowledge, this is the first extensive evaluation method of robotic hand design suitable for dexterity.
This paper proposes a high-speed vehicle trajectory generation algorithm based on graph search. The algorithm utilizes driving patterns for obstacle avoidance to limit nodes of the graph without sacrificing obstacle avoidance performance. Experiments were conducted in simulation and the results showed that the proposed algorithm could generate trajectories for driving 15 seconds ahead in average computation time 0.037 second while the rate of avoided obstacles was 100%.
Previously, we proposed new light irradiation-based drive method of on-chip gel actuator. In our method, on-chip gel actuators are fixed on a glass substrate with light absorbers. Therefore, deformation of the gel is constricted with fixed part and anisotropically deforms in three dimensions. In this study, we evaluate the three-dimensional shapes and drive characteristics of on-chip gel actuator. Furthermore, we evaluate changes of drive characteristics of the actuators with respect to surface area to volume ratio. From this result, we show the possibilities of control of gel deformation and drive characteristics by changing the design of the proposed gel actuator.