Robotic sensing
This article needs to be updated.(August 2022) |
Robotic sensing is a subarea of robotics science intended to provide sensing capabilities to robots. Robotic sensing provides robots with the ability to sense their environments and is typically used as feedback to enable robots to adjust their behavior based on sensed input. Robot sensing includes the ability to see,[1][2][3] touch,[4][5][6] hear[7] and move[8][9][10] and associated algorithms to process and make use of environmental feedback and sensory data. Robot sensing is important in applications such as vehicular automation, robotic prosthetics, and for industrial, medical, entertainment and educational robots.
Vision
Method
Visual sensing systems can be based on a variety of technologies and methods including the use of
Image processing
Image quality is important in applications that require excellent robotic vision. Algorithms based on wavelet transform that are used for fusing images of different spectra and different foci result in improved image quality.[2] Robots can gather more accurate information from the resulting improved image.
Usage
Visual sensors help robots to identify the surrounding environment and take appropriate action.[3] Robots analyze the image of the immediate environment based on data input from the visual sensor. The result is compared to the ideal, intermediate or end image, so that appropriate movement or action can be determined to reach the intermediate or final goal.
Touch
Robot skin
Electronic skin refers to flexible, stretchable and self-healing electronics that are able to mimic functionalities of human or animal skin.[12][13] The broad class of materials often contain sensing abilities that are intended to reproduce the capabilities of human skin to respond to environmental factors such as changes in heat and pressure.[12][13][14][15]
Advances in electronic skin research focuses on designing materials that are stretchy, robust, and flexible. Research in the individual fields of flexible electronics and tactile sensing has progressed greatly; however, electronic skin design attempts to bring together advances in many areas of materials research without sacrificing individual benefits from each field.[16] The successful combination of flexible and stretchable mechanical properties with sensors and the ability to self-heal would open the door to many possible applications including soft robotics, prosthetics, artificial intelligence and health monitoring.[12][16][17][18]
Recent advances in the field of electronic skin have focused on incorporating green materials ideals and environmental awareness into the design process. As one of the main challenges facing electronic skin development is the ability of the material to withstand mechanical strain and maintain sensing ability or electronic properties, recyclability and self-healing properties are especially critical in the future design of new electronic skins.[19]Types and examples
Examples of the current state of progress in the field of robot skins as of mid-2022 are a robotic finger covered in a type of manufactured living human skin,[20][21] an electronic skin giving biological skin-like haptic sensations and touch/pain-sensitivity to a robotic hand,[22][23] a system of an electronic skin and a human-machine interface that can enable remote sensed tactile perception, and wearable or robotic sensing of many hazardous substances and pathogens,[24][25] and a multilayer tactile sensor hydrogel-based robot skin.[26][27]
Tactile discrimination
As robots and prosthetic limbs become more complex the need for sensors capable of detecting touch with high tactile acuity becomes more and more necessary. There are many types of tactile sensors used for different tasks.[28] There are three types of tactile sensors. The first, single point sensors, can be compared to a single cell, or whiskers, and can detect very local stimuli. The second type of sensor is a high spatial resolution sensor which can be compared to a human fingertip and is essential for the tactile acuity in robotic hands. The third and final tactile sensor type is a low spatial resolution sensor which has similar tactile acuity as the skin on one's back or arm.[28] These sensors can be placed meaningfully throughout the surface of a prosthetic or a robot to give it the ability to sense touch in similar, if not better, ways than the human counterpart.[28]
Signal processing
Touch sensory signals can be generated by the robot's own movements. It is important to identify only the external tactile signals for accurate operations. Previous solutions employed the Wiener filter, which relies on the prior knowledge of signal statistics that are assumed to be stationary. Recent solution applies an adaptive filter to the robot's logic.[4] It enables the robot to predict the resulting sensor signals of its internal motions, screening these false signals out. The new method improves contact detection and reduces false interpretation.
Usage
[29] Touch patterns enable robots to interpret human emotions in interactive applications. Four measurable features—force, contact time, repetition, and contact area change—can effectively categorize touch patterns through the temporal decision tree classifier to account for the time delay and associate them to human emotions with up to 83% accuracy.[5] The Consistency Index[5] is applied at the end to evaluate the level of confidence of the system to prevent inconsistent reactions.
Robots use touch signals to map the profile of a surface in hostile environment such as a water pipe. Traditionally, a predetermined path was programmed into the robot. Currently, with the integration of touch sensors, the robots first acquire a random data point; the algorithm[6] of the robot will then determine the ideal position of the next measurement according to a set of predefined geometric primitives. This improves the efficiency by 42%.[5]
In recent years, using touch as a stimulus for interaction has been the subject of much study. In 2010, the robot seal PARO was built, which reacts to many stimuli from human interaction, including touch. The therapeutic benefits of such
Hearing
Signal processing
Accurate audio sensors require low internal noise contribution. Traditionally, audio sensors combine
Robots may interpret strayed noise as speech instructions. Current
Usage
Robots can perceive emotions through the way we talk and associated characteristics and features. Acoustic and linguistic features are generally used to characterize emotions. The combination of seven acoustic features and four linguistic features improves the recognition performance when compared to using only one set of features.[32]
Acoustic feature
Linguistic feature
- Bag of words
- Part-of-speech
- Higher semantics
- Varia
Olfaction
Taste
The electronic tongue is an instrument that measures and compares tastes. As per the IUPAC technical report, an “electronic tongue” as analytical instrument including an array of non-selective chemical sensors with partial specificity to different solution components and an appropriate pattern recognition instrument, capable to recognize quantitative and qualitative compositions of simple and complex solutions[39][40]
In the biological mechanism, taste signals are transduced by nerves in the brain into electric signals. E-tongue sensors process is similar: they generate electric signals as
For example, robot cooks may be able to taste food for dynamic cooking.[41]
Motion perception
Usage
Automated robots require a guidance system to determine the ideal path to perform its task. However, at the molecular scale,
In a
Performance
Efficient robotic exploration saves time and resources. The efficiency is measured by
Non-human senses
Robots may not only be equipped with higher sensitivity and capabilities per sense than all or most[42] non-cyborg humans such as being able to "see" more of the electromagnetic spectrum such as ultraviolet and with higher fidelity and granularity,[additional citation(s) needed] but may also be able have more senses[additional citation(s) needed] such as sensing of magnetic fields (magnetoreception)[43] or of various hazardous air components.[25]
Collective sensing and sensemaking
Robots may share,[44] store, and transmit sensory data as well as data based on such. They may learn from or interpret the same or related data in different ways and some robots may have remote senses (e.g. without local interpretation or processing or computation such as with common types of telerobotics or with embedded[45] or mobile "sensor nodes").[additional citation(s) needed] Processing of sensory data may include processes such as facial recognition,[46] facial expression recognition,[47] gesture recognition and integration of interpretative abstract knowledge.[additional citation(s) needed]
See also
- Applications of artificial intelligence
- Biosensor
- Human-machine system
- Brain-computer interface
- Machine perception
- Remote sensing
- Robotic sensors
- Sensor-based sorting
- Soft robotics
- Timeline of computing 2020–present
References
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- ^ a b Arivazhagan S, Ganesan L, Kumar TGS (Jun 2009). "A modified statistical approach for image fusion using wavelet transform." Signal Image and Video Processing 3 (2): 137-144.
- ^ a b Jafar FA, et al (Mar 2011). "An Environmental Visual Features Based Navigation Method for Autonomous Mobile Robots." International Journal of Innovative Computing, Information and Control 7 (3): 1341-1355.
- ^ a b Anderson S, et al (Dec 2010). "Adaptive Cancelation of Self-Generated Sensory Signals in a Whisking Robot." IEEE Transactions on Robotics 26 (6): 1065-1076.
- ^ a b c d Kim YM, et al (Aug 2010)."A Robust Online Touch Pattern Recognition for Dynamic Human-robot Interaction." IEEE Transactions on Consumer Electronics 56 (3): 1979-1987.
- ^ a b Mazzini F, et al (Feb 2011). "Tactile Robotic Mapping of Unknown Surfaces, with Application to Oil Wells." IEEE Transactions on Instrumentation and Measurement 60 (2): 420-429.
- ^ a b c Matsumoto M, Hashimoto S (2010). "Internal Noise Reduction Using Piezoelectric Device under Blind Condition." Internatl (Jan 2011). "Searching for the most important feature types signalling emotion-related user states in speech." Computer Speech and Language 25 (1): 4-28.
- ^ a b c Lund K, et al (May 2010). "Molecular robots guided by prescriptive landscapes." Nature 465 (7295): 206-210.
- ^ a b Trejos AL, et al (Sep 2009). "Robot-assisted Tactile Sensing for Minimally Invasive Tumor Localization." International Journal of Robotics Research 28 (9): 1118-1133.
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- ^ Barker, Ross (June 1, 2022). "Artificial skin capable of feeling pain could lead to new generation of touch-sensitive robots". University of Glasgow. Retrieved 20 July 2022.
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External links
- Media related to Robotic sensing at Wikimedia Commons