Adaptive cancelation of self-generated sensory signals in a whisking robot

Sensory signals are often caused by one's own active movements. This raises a problem of discriminating between self-generated sensory signals and signals generated by the external world. Such discrimination is of general importance for robotic systems, where operational robustness is dependent on the correct interpretation of sensory signals. Here, we investigate this problem in the context of a whiskered robot. The whisker sensory signal comprises two components: one due to contact with an object (externally generated) and another due to active movement of the whisker (self-generated). We propose a solution to this discrimination problem based on adaptive noise cancelation, where the robot learns to predict the sensory consequences of its own movements using an adaptive filter. The filter inputs (copy of motor commands) are transformed by Laguerre functions instead of the often-used tapped-delay line, which reduces model order and, therefore, computational complexity. Results from a contact-detection task demonstrate that false positives are significantly reduced using the proposed scheme

Human Visual Search Does Not Maximize the Post-Saccadic Probability of Identifying Targets

Researchers have conjectured that eye movements during visual search are selected to minimize the number of saccades. The optimal Bayesian eye movement strategy minimizing saccades does not simply direct the eye to whichever location is judged most likely to contain the target but makes use of the entire retina as an information gathering device during each fixation. Here we show that human observers do not minimize the expected number of saccades in planning saccades in a simple visual search task composed of three tokens. In this task, the optimal eye movement strategy varied, depending on the spacing between tokens (in the first experiment) or the size of tokens (in the second experiment), and changed abruptly once the separation or size surpassed a critical value. None of our observers changed strategy as a function of separation or size. Human performance fell far short of ideal, both qualitatively and quantitatively

The effects of smoking on whisker movements: a quantitative measure of exploratory behaviour in rodents

Nicotine, an important component of cigarette smoke, is a neurotransmitter that contributes to stress, depression and anxiety in smokers. In rodents, it increases anxiety and reduces exploratory behaviours. However, so far, the measurements of exploratory behaviour in rodents have only been semi-quantitative and lacking in sufficient detail to characterise the temporal effect of smoking cessation. As rodents, such as mice and rats, primarily use whiskers to explore their environment, we studied the effect of 3 months smoking with 1 and 2 weeks smoking cessation on whisker movements in mice, using high-speed video camera footage and image analysis. Both protraction and retraction whisker velocities were increased in smoking mice (p<0.001) and returned to normal following just one week of smoking cessation. In addition, locomotion speeds were decreased in smoking mice, and returned to normal following smoking cessation. Lung function was also impacted by smoking and remained impaired even following smoking cessation. We suggest that the increased whisker velocities in the smoking mice reflect reduced exploration and impeded tactile performance. The increase in whisker velocity with smoking, and its reduction following smoking cessation, also lends support to acetylcholine being involved in awareness, attention and alertness pathways. It also shows that smoking-induced behavioural changes can be reversed with smoking cessation, which may have implications for human smokers

Recovering Observability via Active Sensing

Observability is a formal property of a system that ensures the ability to estimate the system’s states from output measurements and knowledge of the inputs. Even when state estimators are not employed, observability is a crucial property in the design of feedback control systems. Engineering sensors are typically designed to guarantee observability irrespective of the control input, thereby simplifying control systems design. Here, we introduce a class of nonlinear sensors that require ‘persistently exciting’ control inputs to maintain observability. This class of sensor models is motivated by biological sensing systems which ‘adapt’ to constant stimuli, giving them a very high dynamic range, but leading to a phenomenon known as perceptual fading. To prevent perceptual fading, animals employ active sensing behaviors in the form of time-varying motor commands that continually stimulate sensory receptors. To capture this phenomenon, we introduce a simplified sensor model that requires similar ‘active’ control inputs to maintain observability. Under certain assumptions, the input–output characteristics of the active sensing system is shown to be equivalent to an observable LTI system. Specifically, we apply three steps to the original (nonlinear) system—(1) modulating via sinusoidal active input, (2) demodulating, and (3) low-pass filtering. The equivalent system is identified by analyzing the Harmonic Transfer Function (HTF) of the modulated system and whose output is then demodulated and low pass filtered. Equivalence of the new observable LTI system and the active sensing system illustrates the potential effectiveness of this framework for active sensing and may pave the way for the design of adaptive sensory systems for engineering applications

Force sensing to reconstruct potential energy landscapes for cluttered large obstacle traversal

Visual sensing of environmental geometry allows robots to use artificial potential fields to avoid sparse obstacles. Yet robots must further traverse cluttered large obstacles for applications like search and rescue through rubble and planetary exploration across Martain rocks. Recent studies discovered that to traverse cluttered large obstacles, multi-legged insects and insect-inspired robots make strenuous transitions across locomotor modes with major changes in body orientation. When viewed on a potential energy landscape resulting from locomotor-obstacle physical interaction, these are barrier-crossing transitions across landscape basins. This potential energy landscape approach may provide a modeling framework for cluttered large obstacle traversal. Here, we take the next step toward this vision by testing whether force sensing allows the reconstruction of the potential energy landscape. We developed a cockroach-inspired, minimalistic robot capable of sensing obstacle contact forces and torques around its body as it propelled forward against a pair of cluttered grass-like beam obstacles. We performed measurements over many traverses with systematically varied body orientations. Despite the forces and torques not being fully conservative, they well-matched the potential energy landscape gradients and the landscape reconstructed from them well-matched ground truth. In addition, inspired by cockroach observations, we found that robot head oscillation during traversal further improved the accuracies of force sensing and landscape reconstruction. We still need to study how to reconstruct landscape during a single traverse, as in applications, robots have little chance to use multiple traverses to sample the environment systematically and how to find landscape saddles for least-effort transitions to traverse

Feeding Kinematics, Suction, and Hydraulic Jetting Performance of Harbor Seals (Phoca vitulina)

The feeding kinematics, suction and hydraulic jetting capabilities of captive harbor seals (Phoca vitulina) were characterized during controlled feeding trials. Feeding trials were conducted using a feeding apparatus that allowed a choice between biting and suction, but also presented food that could be ingested only by suction. Subambient pressure exerted during suction feeding behaviors was directly measured using pressure transducers. The mean feeding cycle duration for suction-feeding events was significantly shorter (0.15±0.09 s; P<0.01) than biting feeding events (0.18±0.08 s). Subjects feeding in-water used both a suction and a biting feeding mode. Suction was the favored feeding mode (84% of all feeding events) compared to biting, but biting comprised 16% of feeding events. In addition, seals occasionally alternated suction with hydraulic jetting, or used hydraulic jetting independently, to remove fish from the apparatus. Suction and biting feeding modes were kinematically distinct regardless of feeding location (in-water vs. on-land). Suction was characterized by a significantly smaller gape (1.3±0.23 cm; P<0.001) and gape angle (12.9±2.02°), pursing of the rostral lips to form a circular aperture, and pursing of the lateral lips to occlude lateral gape. Biting was characterized by a large gape (3.63±0.21 cm) and gape angle (28.8±1.80°; P<0.001) and lip curling to expose teeth. The maximum subambient pressure recorded was 48.8 kPa. In addition, harbor seals were able to jet water at food items using suprambient pressure, also known as hydraulic jetting. The maximum hydraulic jetting force recorded was 53.9 kPa. Suction and hydraulic jetting where employed 90.5% and 9.5%, respectively, during underwater feeding events. Harbor seals displayed a wide repertoire of behaviorally flexible feeding strategies to ingest fish from the feeding apparatus. Such flexibility of feeding strategies and biomechanics likely forms the basis of their opportunistic, generalized feeding ecology and concomitant breadth of diet

A Biologically Inspired Controllable Stiffness Multimodal Whisker Follicle

This thesis takes a soft robotics approach to understand the computational role of a soft whisker follicle with mechanisms to control the stiffness of the whisker. In particular, the thesis explores the role of the controllable stiffness whisker follicle to selectively favour low frequency geometric features of an object or the high frequency texture features of the object.Tactile sensing is one of the most essential and complex sensory systems for most living beings. To acquire tactile information and explore the environment, animals use various biological mechanisms and transducing techniques. Whiskers, or vibrissae are a form of mammalian hair, found on almost all mammals other than homo sapiens. For many mammals, and especially rodents, these whiskers are essential as a means of tactile sensing.The mammalian whisker follicle contains multiple sensory receptors strategically organised to capture tactile sensory stimuli of different frequencies via the vibrissal system. Nocturnal mammals such as rats heavily depend on whisker based tactile perception to find their way through burrows and identify objects. There is diversity in the whiskers in terms of the physical structure and nervous innervation. The robotics community has developed many different whisker sensors inspired by this biological basis. They take diverse mechanical, electronic, and computational approaches to use whiskers to identify the geometry, mechanical properties, and objects' texture. Some work addresses specific object identification features and others address multiple features such as texture and shape etc. Therefore, it is vital to have a comprehensive discussion of the literature and to understand the merits of bio-inspired and pure-engineered approaches to whisker-based tactile perception.The most important contribution is the design and use of a novel soft whisker follicle comprising two different frequency-dependent data capturing modules to derive more profound insights into the biological basis of tactile perception in the mammalian whisker follicle. The new insights into the biological basis of tactile perception using whiskers provide new design guidelines to develop efficient robotic whiskers