By Mark R. Cutkosky, Robert D. Howe (auth.), Subramanian T. Venkataraman, Thea Iberall (eds.)
Manipulation utilizing dextrous robotic arms has been a thrilling but not easy study subject for the final numerous years. whereas major growth has happened within the layout, development, and coffee point keep watch over of robot palms, researchers are up opposed to basic difficulties in constructing algorithms for real-time computations in multi-sensory processing and motor keep watch over. the purpose of this e-book is to discover parallels in sensorimotor integration in dextrous robotic and human fingers, addressing the elemental query of ways the following new release of dextrous palms should still evolve. via bringing jointly experimental psychologists, kinesiologists, computing device scientists, electric engineers, and mechanical engineers, the booklet covers subject matters that variety from human hand utilization in prehension and exploration, to the layout and use of robot sensors and multi-fingered palms, and to regulate and computational architectures for dextrous hand utilization. whereas the final word objective of shooting human hand versatility continues to be elusive, this e-book makes a tremendous contribution to the layout and regulate of destiny dextrous robotic palms via an easy underlying message: a subject matter as complicated as dextrous manipulation may most sensible be addressed via collaborative, interdisciplinary learn, combining excessive point and coffee point perspectives, drawing parallels among human experiences and analytic ways, and integrating sensory info with motor instructions. As visible during this textual content, good fortune has been made during the institution of such collaborative efforts. the long run will delay to expectancies in simple terms as researchers detect advances in parallel fields and as a typical vocabulary emerges from built-in perceptions approximately manipulation.
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Extra resources for Dextrous Robot Hands
Example text
Sterling Bunnell, 1944 ABSTRACT A problem that has plagued both motor psychologists in studying human behavior, and robot designers in reproducing it, is how to quantify that behavior. It has been argued that kinematic and dynamic models are inadequate for explaining human movement unless they also include both the performance constraints and the objectives that affect the neural and neuromuscular inputs. With a dextrous, multi-fingered hand, multiple grasping solutions are possible. This chapter addresses the question faced by the controller, that of how best to use features of the hand to achieve the task goals, given anticipated object properties and predictable interaction outcomes.
However, the response was observed only when the subject's intent was to prevent the glass from falling over. Traub et al argue that this suggests a grab reflex, where the digits respond within a time too short to be voluntary, flexing in order to maintain contact but only if that is the person's intent. In a formal empirical situation, intent emerges from the experimenter's request to the subject to perform a certain task. In MacKenzie et al [1987] for example, the subjects were asked to point with a stylus 'as quickly and as accurately as possible' to a target of varying size and at varying distances.
In the finger pulps, numerous tactile receptors are found, more so than most other parts of the body, thus giving the CNS much information about the object with which they come into contact [Vallbo and Johansson 1984]. These mechanoreceptors are classified by their adaptation response to sustained skin deformation and the structure of their receptive fields. Receptors with small and well-defined receptive fields are especially dense in the finger pulps. Westling and Johansson [1987] observe that at higher grip forces (when the skin is less compliant) these receptors are less responsive.