Kei Senda

Deploy Experiment of Inflatable Tube using Work Hardening

the top of a star shape. The deployment experiments and some finite element method (FEM) analysis show that the pentalpha folding achieves excellent straight-line deployment. In general, creases of the folded inflatable tube are expanded by internal pressure for the desired shape. The inflatable tube should be rigidized after the desired shape is obtained otherwise the shape is lost when the internal pressure reduces. We propose to use work hardening for the subject. The shape of the inflatable tube is kept after the expansion because the influence of creases is erased by the work hardening. An appropriate design of internal pressure, material, and size of the tube is important.

Study on Flapping-of-Wings Flight of Butterfly with Experimental Measurement

This paper treats the flapping-of-wings of a butterfly, which is rhythmic and cyclic motion. The objective of this study is to clarify the principle of a stable flapping-ofwings flight. For the purpose, a dynamics model of a butterfly is derived for analyses by Lagrange’s method, where the butterfly is considered as a rigid multi-body system. A simple method and a vortex method are then applied to make a simulator where the methods calculate the aerodynamic force. An experimental system with a low-speed wind tunnel is constructed for fundamental data of flapping-of-wings motion, where the system measures the aerodynamic force and the motion simultaneously by a measure and a optical measurement system. Validity of the mathematical model is examined by comparing the measured data with the numerical results. A periodic orbit of a flapping-of-wings flight is searched so as to fly the butterfly model. Furthermore, numerical simulations show that the flapping-of-wings motion is instable.

Study on Flapping-of-Wings Flight of Butterfly with Numerical and Experimental Analysis

This paper treats the flapping-of-wings flight of a butterfly, which is rhythmic and cyclic motion. The objective of this paper is to clarify the principle of stabilization of the flapping-of-wings flight. For the purpose, this study performs the experiment for the quantitative data acquisition and qualitative observation, derives models of a butterfly, and compares the actual and modeled butterflies. An experimental system with a low-speed wind tunnel is constructed for fundamental data of flapping-of-wings motion, where the system measures the aerodynamic force and the motion simultaneously by a measure and a optical measurement system. The measured data of flapping motion shows what degreeof-freedom are used for butterfly control. A dynamics model of a butterfly is derived for analyses by Lagrange’s method, where the butterfly is considered as a rigid body system. For the aerodynamic forces, a lumped-vortex method and a panel method are applied. Validity of the mathematical model is examined by comparing the measured data with the numerical results. A periodic orbit of a flapping-of-wings flight is searched so as to fly the butterfly model. Both models in the flapping-of-wings flight are unstable. The unstable level of the panel method model becomes small by considering free-vortices in wakes. It is shown that the wake-induced flow of the panel method has a kind of feedback stabilization eect.

Stabilization of Flapping-of-Wings Flight of a Butterfly, Considering Wakes

This paper studies the flapping-of-wings flight of a butterfly, which is rhythmic and cyclic in motion. The objective is to clarify the principle of stabilization of the flapping-of-wings flight. For this purpose, an experimental system with a low-speed wind tunnel is constructed for fundamental data of flapping-of-wings motion, where the system measures the aerodynamic force and the motion simultaneously using a measure and an optical measurement system. A dynamics model of a butterfly is derived by Lagrange’s method, where the butterfly is considered as a rigid body system. For the aerodynamic forces, a lumped-vortex method and a panel method are applied. Validity of the mathematical models is examined by the good agreement of the numerical results with the measured data. Then, periodic orbits of a flapping-of-wings flight are searched in order to fly the butterfly models. Almost periodic orbits are obtained, but both models in the flapping-of-wings flight are unstable. The unstable level of the panel method model is smaller by considering free-vortices in wakes. Meaning that the wake-induced flow has a type of feedback stabilization effect.

Motion Measurement of Inflatable Tube from Video Images

This study is concerned with a method of the image measurement using video cameras to measure deploying behavior of inflatable tube in deployment experiments. This system measures the motion of the creases for folding on the inflatable tube. Moreover, the extended SNAKES technique with a structural model enables measurement with high accuracy. The image measurement is performed for the deploying behavior of the inflatable tube folded by the pattern called a pentalpha folding. First, to measure the deployingt behavior of an inflatable tube, the system with two cameras in the laboratory is developed. Image measurement is achieved with good accuracy by using synchronized cameras with small optical aberration and calibration with good accuracy. Next, a measurement system is developed for the deployment experiment of the inflatable tube in the microgravity environment using the aircraft parabolic flight. In the aircraft experiment, there were various restrictions, e.g. asynchronous six cameras with large optical aberration. In addition, calibration in the flight condition was not available. Using three sets of stereo cameras with six cameras and integrating the obtained images, we measure the deploying behavior of the entire tube after the difficulties on the image measurement are overcome. This paper reports on the result of the obtained image measurement.

A study toward cognitive action with environment recognition by a learning space robot

This paper addresses an experimental system simulating a free-flying space robot, which has been constructed to study autonomous space robots. The experimental system consists of a space robot model, a frictionless table system, a computer system, and a vision sensor system. The robot model is composed of two manipulators and a satellite vehicle, and can move freely on a two-dimensional planar table, without friction, using air-bearings. The robot model has successfully performed the automatic truss structure assembly, including many jobs, e.g., manipulator berthing, component manipulation, arm trajectory control collision avoidance, assembly using force control, etc. Moreover, even if the robot fails in a task planned in advance, the robot re-plans the task by using reinforcement learning, and obtains the task goal for basically kinematic problems. But, for a class of complicated dynamic problems, the computational periods and efforts are infeasible for on-line learning. Some approaches are proposed to accelerate the learning speed, which also give models of cognitive actions and approaches to so-called a frame problem. The experiment demonstrates the possibility of the autonomous construction and the usefulness of space robots.

Reinforcement learning accelerated by using state transition model with robotic applications

This paper discusses a method to accelerate reinforcement learning. Firstly defined is a concept that reduces the state space conserving policy. An algorithm is then given that calculates the optimal cost-to-go and the optimal policy in the reduced space from those in the original space. Using the reduced state space, learning convergence is accelerated. Its usefulness for both DP (dynamic programming) iteration and Q-learning are compared through a maze example. The convergence of the optimal cost-to-go in the original state space needs approximately N or more times as long as that in the reduced state space, where N is a ratio of the state number of the original space to the reduced space. The acceleration effect for Q-learning is more remarkable than that for the DP iteration. The proposed technique is also applied to a robot manipulator working for a peg-in-hole task with geometric constraints. The state space reduction can be considered as a model of the change of observation, i.e., one of cognitive actions. The obtained results explain that the change of observation is reasonable in terms of learning efficiency.