Analysis, modeling and experimental validation of temperature-changing effect
on mechanical properties of pneumatic artificial muscle
Guolei Wang , Xiaotong Hua , Jing Xu , Libin Song and Ken Chen
Depar tment of M echanical Engineering, Tsinghua Universit y, Beijing, People’s Republic of China
ABSTR AC T
This paper focuses on quantify how temperature affects the mechanical properties of pneumatic artificial muscle (PAM). The influence of temperature variations on PAM’s structure size and internal friction was analyzed firstly, based on the thermal characteristics of rubber diaphragm and fiber mesh, then a novel model considering the influence of temperature variation is proposed, without any fitting parameter or any parameter with uncertain physical meanings. In order to verify the proposed model, temperature-rising experiments using heating device and continuous operation were both carried out separately. Through the comparison of characteristic curves under different temperatures, PAM’s characteristics were proven to be affected by temperature variations. The results show that inside temperature changing of PAM is why there are drifting and time-varying phenomenon of their mechanical characteristics in long-term operation, and the proposed model can predict the variations caused by temperature changing well. Meanwhile, the accuracy of the new model is higher than Chou model and lower than Andrikopoulos model; it is understandable because our new model has no fitting parameters, but the advantage of new model is that it takes temperature as independent variables and, therefore, can be used at different temperatures directly without any
calibration.
KEY WORDS
Pneumatic ar tificial muscle; model; thermodynamic
Hand waving in command spaces: a framework for operating home appliances
Takumi Kanoa, Takuya Kawamurab, Hidetsugu Asanoc, Takeshi Nagayasua and Kazunori Umedab
aCourse of Precision Engineering, Chuo University, Tokyo, Japan; bDepartment of Precision Mechanics, Chuo University, Tokyo, Japan; cResearch & Development Division, Pioneer Corporation, Saitama, Japan
ABSTR AC T
In this paper, hand waving in a ‘command space’ is proposed as a new framework for operating home appliances. A command space is associated with the operation of a home appliance; an operation is retrieved by waving a hand in the command space. A home appliance operation system with the function of multiplexing command space modules and integrating multiple commands is constructed. With the proposed framework and system, home appliance operation is possible only by hand waving, an intuitive gesture for a human. Experiments were conducted that verified that complex operations, such as scheduling the recording of a TV program, can be performed with the system. The usability of the constructed system is evaluated using Brooke’s System Usability
Scale (SUS). The average SUS score was 66.8, which indicates that the subjects had relatively positive impression on the system in spite of long operation time.
KEY WORDS
Gesture recognition; human interface; image processing; intelligent room; command space
Hierarchical reinforcement learning of multiple grasping strategies with human
instructions
T . O s a a ,b, Jan Petersc,d and G. Neumanne
aUniversity of Tokyo, Tokyo, Japan; bRIKEN, Tokyo, Japan; cTechnische Universität Darmstadt, Darmstadt, Germany; dMax-Planck Institute, Tübingen, Germany; eUniversity of Lincoln, Lincoln, UK
ABSTR AC T
Grasping is an essential component for robotic manipulation and has been investigated for decades. Prior work on grasping often assumes that a sufficient amount of training data is available for learning and planning robotic grasps. However, constructing such an exhaustive training dataset is very challenging in practice, and it is desirable that a robotic system can autonomously learn and improves its grasping strategy. Although recent work has presented autonomous data collection through trial and error, such methods are often limited to a single grasp type, e.g. vertical pinch grasp. To address these issues, we present a hierarchical policy search approach for learning multiple grasping strategies. To leverage human knowledge, multiple grasping strategies are initialized with human demonstrations. In addition, a database of grasping motions and point clouds of objects is also autonomously built upon a set of grasps given by a user. The problem of selecting the grasp location and grasp policy is formulated as a bandit problem in our framework. We applied our reinforcement learning to grasping both rigid and deformable objects. The experimental results show that our framework autonomously learns and improves its performance through trial and error and can grasp previously unseen objects with a high accuracy.
KEY WORDS
Hierarchical reinforcement learning; grasping; point clouds; active learning
Position/torque hybrid control of a rigid, high-gear ratio quadruped robot
Okkee Sim , Taejin Jung, Kang Kyu Lee, Jaesung Oh and Jun-Ho Oh
Mechanical Engineering, Korea Advanced I nstitute of S cience & Technology, Daejeon, S outh Korea
ABSTR AC T
In this study, we introduce position/torque hybrid control for a newly designed rigid and high-gear ratio quadruped robot. The Experimental results indicated that the use of this control strategy allows the quadruped robot to maintain its stability while walking, and foot contact can be stabilized with only knee torque control and other joints are position controlled, without contact force feedback. Additionally, we suggested a smooth pattern connection method within or from preview control to the center of mass natural dynamics, and vice versa. We validated the proposed control strategies by conducting experiments.
KEY WORDS
I nverse dynamics control; quadruped walk ing; high gear rat i o ; hy bri d co nt ro l; p re v i e w co nt ro l
