Whiskered robots

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Figure 1: Biomimetic whiskered robots.

Whiskered robots This article will briefly cover: Whiskered robots that carry out active touch for object shape and texture discrimination


Contents

Overview

Touch is currently an under utilised sensory mode in robotics, with vision remaining the prefered method of spatial exploration. There are many examples in the animal kingdom of creatures that live in environments where a developed sense of touch rather vision is advantagous for survival, i.e., in confined and visually occluded spaces. Such environments also feature in the operational requirement of certain robotic platforms, which, in part, justifies a biomimetic approach to the investigation and evaluation of artificial touch sensors. Perhaps more persuasively, there are also situations, for animals and robots, where a developed sense of touch would be a beneficial complement, rather than replacement, for vision. In this article the use of whiskers as a method of endowing robots with a sense of touch is addressed. An initial discussion about the advantages of a biomimetic approach in the development of whiskered robots is followed by a summary of the history of whiskered robot research. The final section of this article will focus on the more recent developments and contributions that have been made to the field, focussing on the two way exchange of ideas and observations between engineers and biologists.


Biomimetic whiskers

The use of whiskers to effectively derive tactile information from the environment gives rise to a number of lines of enquiry that are of equal importance to both engineers and biologists. From an engineering persepctive, one issue is to identify any advantages of using whiskers for tactile exploration over other approaches, for example, based more directly on human touch. By observing whisker development \cite{sullivan}, array morphology \cite{brecht}, and how animals position and move their whiskers during natural exploratory behaviour \cite{Grant}, we can intuit advantages such as robustness, speed of response and size of sensory field, and measure fine spatial accuity \cite{ahissar} and ability to determine intricate surface features \cite{carvell}. Other more specific questions that are generated through the development of an engineering specification have inspired further biological investigation. For example, to determine how to move an artificial array of whiskers to most effectively gather information from the environment, video footage of rat whisking has been analysed to develop posits for possible control strategies\cite{Mitchinson}. Intriguingly, these model control strategies can then be physically tested using the robotic artefact \cite{Pearson} to inspire further investigation of the original biological analogue, i.e., how to deal with noise generates by self-motion \cite{Andersson}. This biomimetic design approach that includes the two-way exchange of ideas and skills, can be applied to many areas of the design of a useful whisker based sensory system. In addition to modelling the physical mechanics of whiskers to develop a sensory tool for robotics, whiskers also act as extremely powerful ``probes with which to observe the function of the brain. The neural components of the whisker sensory system of the rat maintain an exquiste degree of topological perservation from whisker follicle through to cortex \cite{Kleinfeld}. This allows for controlled observations of the neural response to stimuli applied to the whisker shaft at multiple levels of this neuraxis. Model systems can be constructed from such observations which are then reinforced, or at least validated, by behavioural observations of the animal, an approach known as neuroethology \cite{Camhi}. Using robotic artefacts to test such models (computational neuroethology \cite{Beer}) introduces a degree of experimental flexibility to allow experiments that may be either impossible or unethical to achieve through animal testing. It also provides roboticists the opportunity to work with neuroscientists to evaluate novel brain-based control approaches for future autonomous robotic systems \cite{seth}.


History

Whisker based sensors have been used on mobile robots since the mid 1980's. Initially they were used as simple binary proximity sensors to assist in navigation and obstacle avoidance \cite{Russell.1984}, \cite{Brooks.1989}, \cite{Hirose.1990}. Examples of whiskers used on robots for more detailed spatial exploration can be divided into either active or passive touch approaches. Active touch whiskers measure the bending torque of the whisker as it makes contact with objects during a controlled movement, analogous to the whisking behaviour of rats \cite{Snyder.1990}, \cite{Ueno.1994}, \cite{Kaneko.1998}. Passive touch whiskers measure the torque of whisker bend in response to contacts made with objects as the platform on which the whiskers are mounted moves passed them, i.e., the whiskers are not `directly' actuated. For example spring loaded potentiometers have been extensively used to measure this torque \cite{Russell.1992} \cite{Jung.1996}, \cite{Wijaya.2002}. Further examples of passive touch based whisker sensors applicable to mobile robotics include \cite{Brock.1987} and \cite{Tsujimura.1989}. More recent examples of active whisker sensors for surface inspection utilise load cells to measure the whisker deflection torque \cite{Clements.2006}, whilst others use resonating piezoelectric stimulators \cite{Muraoka.2005} or strain gauges \cite{Solomon.2006}. There are a limited number of examples of more biologically plausible whisker sensory arrays installed on mobile robots to conduct studies of a more biomimetic nature. aMOUSE project, Darwin IX robot project, Whiskerbot project, ICEA project, BIOTACT project\\



State of the art

References

  • Albero, Antony (1999). Pizza Margherita. Journal of pizza eaters 19(3): 13. arXiv:0808.000
  • Albero, Antonio and Bocca, Bill (2001). Pizza Capricciosa. Journal of pizza eaters 27: 121-127. arXiv:0808.000
  • Albero, Antonio; Bocca, Bill and Cuoco, C T (2003). Pizza Quattro Stagioni. Journal of pizza eaters 34(4): 12.
  • Albero, Antonio; Bocca, Bill; Cuoco, C T and Dude, David B (2007a). Pizza Napoletana. Journal of pizza eaters 37: 121-127.
  • Albero, Antonio; Bocca, Bill; Cuoco, C T; Dude, David and Elica, E Q (2007b). Pizza Marinara. Journal of pizza eaters 43(4): 1-13.
  • Albero, Antonio et al. (2008). Pizza Piccante. Journal of pizza eaters 45(5): 1-13.
  • Alto, Antony (1999). La Pizza! Mangiare bene, Volume 3. Albero and Bacca editors. Food Publishers, Genoa.
  • Alto, Antony and Bocca, Bill (2000). La Pasta! Mangiare bene. Albero editor. Food Publishers, Genoa. Chapter 1.
  • Alto, Antony; Bocca, Bill and Cuoco, C T (2002). Pizza: prepare it yourself. Food Publishers, Genoa. Page 22. ISBN 1-234-99929-0.
  • Alto, Antony; Bocca, Bill; Cuoco, C T and Dude, David B (2005a). Italian Pizza. Food Publishers, Genoa.
  • Alto, Antony; Bocca, Bill; Cuoco, C T; Dude, David B and Elica, E Q (2005b). Napolitan Pizza. Food Publishers, Genoa.
  • Alto, Antony et al. (2005c). American Pizza. Food Publishers, Genoa.

Further reading

  • Magro, C T (2008). Pizza: a danger for health? Food Publishers, Paris. page 22. ISBN 1-234-90929-0. This reference is unreliable in conclusions, but quite accurate in its introduction.
  • Izhikevich, E M (2007). Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting The MIT Press, Cambridge, MA. ISBN 0262090430. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience.

External links

Eugene M. Izhikevich website

See also

Brain, Neuron, Scholarpedia:Instructions for authors

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