Estimating an articulated tool's kinematics via visuo-tactile based robotic interactive manipulation

Li Q, Ückermann A, Haschke R, Ritter H. Estimating an articulated tool's kinematics via visuo-tactile based robotic interactive manipulation. Presented at the IEEE IROS, Madrid,Spain.The usage of articulated tools for autonomous robots is still a challenging task. One of the difficulties is to automatically estimate the tool’s kinematics model. This model cannot be obtained from a single passive observation, because some information, such as a rotation axis (hinge), can only be detected when the tool is being used. Inspired by a baby using its hands while playing with an articulated toy, we employ a dual arm robotic setup and propose an interactive manipulation strategy based on visual-tactile servoing to estimate the tool’s kinematics model. In our proposed method, one hand is holding the tool’s handle stably, and the other arm equipped with tactile finger flips the movable part of the articulated tool. An innovative visuo-tactile servoing controller is introduced to implement the flipping task by integrating the vision and tactile feed- back in a compact control loop. In order to deal with the temporary invisibility of the movable part in camera, a data fusion method which integrates the visual measurement of the movable part and the fingertip’s motion trajectory is used to optimally estimate the orientation of the tool’s movable part. The important tool’s kinematic parameters are estimated by geometric calculations while the movable part is flipped by the finger. We evaluate our method by flipping a pivoting cleaning head (flap) of a wiper and estimating the wiper’s kinematic parameters. We demonstrate that the flap of the wiper is flipped robustly, even the flap is shortly invisible. The orientation of the flap is tracked well compared to the ground truth data. The kinematic parameters of the wiper are estimated correctl

Review on human‐like robot manipulation using dexterous hands

In recent years, human hand‐based robotic hands or dexterous hands have gained attention due to their enormous capabilities of handling soft materials compared to traditional grippers. Back in the earlier days, the development of a hand model close to that of a human was an impossible task but with the advancements made in technology, dexterous hands with three, four or five‐fingered robotic hands have been developed to mimic human hand nature. However, human‐like manipulation of dexterous hands to this date remains a challenge. Thus, this review focuses on (a) the history and motivation behind the development of dexterous hands, (b) a brief overview of the available multi‐fingered hands, and (c) learning‐based methods such as traditional and data‐driven learning methods for manipulating dexterous hands. Additionally, it discusses the challenges faced in terms of the manipulation of multi‐fingered or dexterous hands

Industrial Robotics

This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein