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Robotics and Neuroscience Review Current Biology 24, R910–R920, September 22, 2014 ª2014 Elsevier Ltd All rights reserved http://dx.doi.org/10.1016/j.cub.2014.07.058 Robotics and Neuroscience Review Dario Floreano1,*, Auke Jan Ijspeert2, and Stefan Schaal3 under study become physical models to test hypotheses. In the following sections we will examine to what extent neuro- science and robotics have resulted in novel insights and In the attempt to build adaptive and intelligent machines, devices in the specific fields of invertebrates, vertebrates, roboticists have looked at neuroscience for more than and primates. half a century as a source of inspiration for perception and control. More recently, neuroscientists have resorted Invertebrates to robots for testing hypotheses and validating models of Invertebrates produce more stereotyped behaviours and are biological nervous systems. Here, we give an overview of easier to manipulate than most vertebrates, making them the work at the intersection of robotics and neuroscience suitable candidates for embodiment of neuronal models in and highlight the most promising approaches and areas robots [7]. where interactions between the two fields have generated significant new insights. We articulate the work in three Perception sections, invertebrate, vertebrate and primate neurosci- Insect behaviour largely depends on external stimulation of ence. We argue that robots generate valuable insight into the perceptual apparatus, which triggers basic reactions the function of nervous systems, which is intimately linked such as attraction and evasion. Mobile robots have been to behaviour and embodiment, and that brain-inspired often used to understand the neural underpinnings of taxis, algorithms and devices give robots life-like capabilities. movement towards or away from a stimulus source. For example, Webb and Scutt [8] resorted to a mobile robot Introduction equipped with a bio-mimetic bilateral acoustic apparatus Intelligent robots are behavioural agents that autonomously to disambiguate between two different neuronal models of interact with their environment through sensors, actuators, cricket phonotaxis whereby females can discriminate and and a control system producing motor actions from sensory approach conspecific males that produce species-specific data. Interestingly, what is today considered the first auton- songs. The authors showed that two spiking neurons repli- omous robot [1] was built in the early 1950s by neurophysiol- cating the temporal coding properties of identified auditory ogist William Grey Walter [2], to show that complex, neurons were sufficient to reproduce a large variety of pho- purpose-driven behaviours can be produced by few inter- notactic behaviours observed in real crickets, supporting connected neuron-like analog electronic devices that close the hypothesis that recognition and localization of a singing the loop between perception and action in a situated and cricket does not require two separate neuronal mechanisms. embodied system (see, https://www.youtube.com/watch? Chemotactic behaviour of invertebrates has been studied v=lLULRlmXkKo). Along this line of thought, thirty years later in a variety of contexts. For example, Grasso et al. [9] used an the neuroanatomist Valentino Braitenberg [3] conceived a underwater robot to test and discriminate between different series of imaginary vehicles with simple sensors and wirings neuroethological hypotheses of how lobsters detect and inspired by universal properties of nervous systems and navigate towards the source of a chemical plume in turbulent argued that the resulting behavioural complexity originated water. The robot was designed to accurately model the from the interaction with the environment rather than from dimension of the lobster and its chemical sensor layout, the complexity of the brain, and that traditional analysis of while the locomotion system was abstracted as a pair of nervous systems can learn from the ‘synthesis’ (construc- wheels. Similarly, Pyk et al. [10] used wheeled and flying tion) of behavioural systems. Indeed, nervous systems robots equipped with bio-mimetic chemical sensors to cannot be understood in isolation from body and behaviour, falsify a neuronal hypothesis of moth chemotactic behaviour because physical properties (mass, springs, temporal de- and propose an alternative hypothesis. lays, friction, etc.) significantly alter the behavioural effects Robots have also been used to investigate the neural of neural signals and affect the co-evolution and co-develop- mechanisms that allow flying insects to navigate in complex ment of brains and bodies [4]. Consequently, it has been environments with a compound eye radically different from argued that understanding brains requires the joint analysis vertebrate eyes, featuring coarse spatial resolution, fixed and synthesis of relevant parts of the body, environment focus, and almost complete lack of stereovision. Models of and neural systems [5]. Understanding motor control re- those neural mechanisms have also led to the development quires understanding a series of specific transformations of vision-based control of robot drones flying near the from neural signals to musculoskeletal systems to the ground or in cluttered environments [11]. Insects rely on environment where the complexity of animal bodies may image motion generated by their own movement to avoid simplify, instead of complicating, control [6]. In this context, obstacles, regulate speed and latitude, chase, escape and robots incorporating the biomechanics of the animal system land [12,13]. There is a mathematical correspondence be- tween the amplitude of image motion, also known as optic flow, and the distance to corresponding objects when the 1Laboratory of Intelligent Systems, Ecole Polytechnique Fe´ de´ rale de viewer translates on a straight line, but not when it rotates Lausanne, Station 11, Lausanne, CH 1015, Switzerland. 2Biorobotics [14]. It has been speculated that freely flying flies follow Laboratory, Ecole Polytechnique Fe´ de´ rale de Lausanne, Station 14, straight lines interrupted by rapid turns, during which visual Lausanne, CH 1015, Switzerland. 3Max-Planck-Institute for Intelligent signals are suppressed, in order to estimate distances using Systems, Spemannstrasse 41, 72076 Tu¨ bingen, Germany, & University translational optic flow [15]. This hypothesis was tested of Southern California, Ronald Tutor Hall RTH 401, 3710 S. McClintock by Franceschini, Pichon, Blane` s and Brady [16], using a Avenue, Los Angeles, CA 90089-2905, USA. wheeled robot equipped with a circular array of compound *E-mail: Dario.Floreano@epfl.ch eyes, whose analog electronics mimicked the elementary Special Issue R911 motion detection circuitry of visual neurons. This robot could perform collision-free navigation in a cluttered environment by moving along straight lines interrupted by sharp avoid- ance rotations during which visual information was ignored. In another study, Srinivasan et al. [17] argued that, as the angular velocity of the image projected on the ventral side of the insect is proportional to the ratio between horizontal speed and height, insects regulate their speed by maintain- ing a constant image motion, which results in graceful deceleration during landing. The hypothesis that a simple mechanism of optic flow regulation could be used to control altitude and landing without explicitly measuring distance to the ground was validated with helicopters equipped with two artificial ommatidia pointing towards the ground. The same optic flow regulator was then shown to be effective to repro- duce a variety of other behaviours observed in insects, such as terrain following and corridor centering [18]. It has also been shown that optic flow regulation of collision-free navi- gation and altitude control in indoor [19] and outdoor [20] free-flying drones (Figure 1) can be achieved by making roll and pitch angles dependent on two weighted sums of optic flow intensities — a simple operation that could be accomplished by wide-field visual neurons in the lobula plata complex of the insect brain. Indeed, Humbert et al. [21] pro- posed the hypothesis that wide-field tangential cells in the visual system of insects are not used to estimate self-motion, as previously argued, but to detect discrepancies between desired and observed optic flow, and use these discrep- ancies to correct navigation in a feedback loop. The authors successfully tested this hypothesis on a micro-helicopter using analog very large-scale integration (VLSI) sensors and models of the tangential neurons flying in textured environments. Figure 1. Drones with insect-like vision. Insect compound eyes have also inspired the develop- ment of novel types of tiny cameras capable of unparalleled (A) An indoor vision-based drone developed by Zufferey et al. [19] at EPFL is equipped with linear camera facing forward (d), linear camera fields of view with no angular distortion. Recently, two facing downward (c), propeller (a), anemometer (e), rudder and ailerons different designs of miniature artificial compound eyes (b), and battery (f). (B) An outdoor vision-based drone developed by have been proposed. Song et al. [22] described an hemi- Beyeler et al. [20] at EPFL is equipped with seven optic flow sensors spherical compound eye combining elastomeric compound pointing left, left-down, down, right-down, and right. (Reproduced optics with deformable arrays of thin silicon photodetectors from [20] with kind permission from Springer Science and Business that could be shaped into
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