Casting manipulation has been studied to expand the robot's movable range. In this manipulation, the robot throws and reaches the end effector to a distant target. Usually, a special casting manipulator, which consists of rigid arm links and specific flexible linear objects, is constructed for an effective casting manipulation. However, the special manipulator cannot perform normal manipulations, such as picking and placing, grasping, and operating objects. We propose that the normal robot arm, which can perform normal tasks, picks up an unknown string in the surrounding environment and realizes casting manipulation with it. As the properties of the string are not provided in advance, it is crucial how to reflect it in casting manipulation. This is realized by the motion generation of the robot arm with the simulation of string movement, actual string manipulation by the robot arm, and string parameter estimation from the actual string movement. After repeating these three steps, the simulated string movement approximates the actual to realize casting manipulation with the unknown string. We confirmed the effectiveness of the proposed method through experiments.
We propose a method to realize the dynamic manipulation of a string with unknown characteristics via a high-speed robot arm. We use a mass-spring-damper model for the string and repeat three steps: motion generation, real manipulation, and parameter estimation. Robot motion is given by the joint angular velocities expressed by the Bezier curves. Their control points are randomly positioned to generate various robot motion for dynamic string manipulation. The generated motion is performed by a wire-driven robot arm and, real string movement is captured by the camera. These time-series images are used for the parameter estimation of string. The best parameter set is determined via comparison between real and simulated string movement after changing parameter randomly and logarithmically. This parameter set is not unique, but it simulates the actual string movement well. Since the estimated string parameter is used for the robot motion generation after repeating the above 3 steps, the motion generation reflects string property and motion objective can success without special tests in advance. This is an advantage of our method because it is difficult to know all of string property with very complicated non-linearity beforehand. We focus on realizing the momentary string shape in 2 dimensions in this paper. We confirmed the effectiveness of our proposed method by realizing five momentary shapes and 3 kinds of string properties. We also discussed the reproducibility and compatibility of estimated parameters and motion generation.
Dynamically manipulating flexible objects using robots is difficult. Some studies have been conducted that only considered one type of object with known properties or that needed an identification test for string properties in advance. We propose a method to realize the dynamic manipulation of a string with unknown characteristics. We use a mass-spring-damper model for the string and repeat three steps: motion generation, real manipulation, and parameter estimation. The proposed method estimates the string properties to realize the motion objective via the real manipulation of the string. An identification test in advance was not necessary. In this study, we focus on swing manipulation. This can increase the motion energy of a string without a high-power actuator. After making a large swing, the robot can throw strings to a more distant target, such as a hammer throw. This motion is useful for explanation robots, rescue robots, and so on. We modified the proposed method to generate a swing manipulation. Then, we investigate whether swing manipulation can be performed by the proposed method and demonstrate its effectiveness via experiments with various strings with unknown characteristics.
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