Abstract
Abstract There are many applications involving robotic hands in which teleoperation-based approaches are preferred to autonomous solutions. The main reason is that cognitive skills of human operators are desirable in some task scenarios, in order to overcome limitations of robotic hands abilities in dealing with unstructured environments and/or unpredetermined requirements. In particular, in this work we focus on the use of anthropomorphic grasping devices and, specifically, on their teleoperation based on movements of the human operator’s hand (the master hand.) Indeed, the mapping of human hand configurations to an anthropomorphic robotic hand (the slave device) is still an open problem, because of the presence of dissimilar kinematics between master and slave that produce shape and/or Cartesian errors – as addressed within our study. In this work, we propose a novel algorithm that combines joint and Cartesian mappings in order to enhance the preservation of both finger shapes and fingertip positions during the teleoperation of the robotic hand. In particular, a transition between the joint and Cartesian mappings is realized on the basis of the distance between the fingertip of the master hands’ thumb and the opposite fingers, in which the mapping of the thumb fingertip is specifically addressed. The result of the testing of the algorithm with a ROS-based simulator of a commercially available robotic hand is reported, showing the effectiveness of the proposed mapping.
Highlights
These methods try to increase the intuitiveness of control for the operator and have proved to be effective in grasping operations (Colasanto et al, 2012)
The phalanx lengths of the Allegro Hand are clearly longer than standard human phalanges,well spreading the shape and Cartesian errors illustrated in Fig. 2, and making this robotic hand a likely real case of a commercial device on which a user can benefit from the proposed teleoperation mapping
As it is possible to observe from the simulation results of Fig. 6, the master hand gestures were reproduced more faithfully by the proposed mapping algorithm with respect to the joint-only and Cartesian-only mappings, the latter two introducing shape and Cartesian errors in the robotic hand The reason of this is thatthe cartesian mapping is applied only to the slave fingers whose related master hands’ fingertips enter within a sphere centered in the thumb fingertip, i.e.: the green sphere in Fig. 6, corresponding to the sphere with radius r1 in Subsec. 2.3
Summary
These methods try to increase the intuitiveness of control for the operator and have proved to be effective in grasping operations (Colasanto et al, 2012). No studies have taken into account the preservation – on the robotic hand – of the distance between the master hand’s thumb and finger fingertips when a precise teleoperation is desired by the operator. Instead, such an aspect is essential in almost the totality of the activities that require an accurate positioning of the hand fingertips (Kuo et al, 2009) and – we claim – for the overall sense of controllability, and even embodiment (Paulos and Canny, 1998) of the teleoperated grasping device. The article is organized as follows: in Sec. 2 the teleoperation shape and Cartesian errors are introduced, and the proposed mapping algorithm is illustrated; Sec. 3 reports the results of simulation experiments and Sec. 4 outlines conclusions and future work directions
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