Цифровые беспроводные технологии для оценки показателей сельскохозяйственной техники

When testing agricultural machinery in order to determine its functional indicators, the ability to wirelessly transmit data between sensors, measuring and information systems are important. (Research purpose) To develop methods and create wireless digital devices for determining the functional indicators of agricultural tractors and machines with the ability to wirelessly transmit data to a remote control point in real time. (Materials and methods) The authors assumed that it was possible to determine the slipping of driving wheels using an inertial navigation system. It was found that in order to calculate real-time indicators obtained using wireless technologies, it was necessary to determine the characteristics of the input signals of discrete sensors on the side of the measuring system. (Results and discussions) The authors substantiated a method for determining the period of incoming signals of discrete sensors with an accuracy of 0.001 seconds for wireless information transmission. They proposed the design of a slipping sensor for an energy vehicle driving wheels, the main element of which is an inertial wheel position sensor. They developed a discrete signal input module and an inertial slipping sensor with the possibility of wireless data transmission based on a radio system with a carrier frequency of 433 megahertz. During field tests, it was found that the accuracy of determining slippage using the inertial wireless sensor IP-291 does not exceed 1 percent; the range of stable radio communication from the tested object to the test control center reaches 1000 meters; the current indicators obtained through digital radio communication did not differ from the indicators obtained in the tractor cab. (Conclusions) The authors worked out an effective system for wireless information transfer with the ability to calculate the performance of the tested equipment in real time.При проведении испытаний сельскохозяйственной техники с целью определения ее функциональных показателей важное значение имеет возможность беспроводной передачи данных между датчиками, измерительной и информационной системами. (Цель исследований) Разработать методы и создать беспроводные цифровые устройства для определения функциональных показателей сельскохозяйственных тракторов и машин с возможностью беспроводной передачи данных на удаленный пункт контроля в режиме реального времени. (Материалы и методы) Предположили, что определить буксование ведущих колес возможно с помощью инерциальной навигационной системы. Установили, что для расчета показателей в реальном режиме времени, полученных с помощью беспроводных технологий, необходимо определить характеристики входящих сигналов дискретных датчиков на стороне измерительной системы. (Результаты и обсуждение) Обосновали метод определения периода входящих сигналов дискретных датчиков с точностью 0,001 секунды для беспроводной передачи информации. Предложили конструкцию датчика буксования ведущих колес энергосредства, основным элементом которого является инерциальный датчик положения колеса. Разработали модуль ввода дискретных сигналов и инерциальный датчик буксования с возможностью беспроводной передачи данных на базе радиосистемы с несущей частотой 433 мегагерц. В ходе полевых испытаний установили, что точность определения буксования с помощью инерциального беспроводного датчика ИП-291 не превышает одного процента; дальность устойчивой радиосвязи от испытываемого объекта до пункта управления и контроля за испытаниями достигает 1000 метров; текущие показатели, поступившие посредством цифровой радиосвязи, не отличались от данных, полученных в кабине трактора. (Выводы) Создали эффективную систему беспроводной передачи информации с возможностью расчета показателей испытываемой техники в режиме реального времени

A model-free approach to fingertip slip and disturbance detection for grasp stability inference

Robotic capacities in object manipulation are incomparable to those of humans. Besides years of learning, humans rely heavily on the richness of information from physical interaction with the environment. In particular, tactile sensing is crucial in providing such rich feedback. Despite its potential contributions to robotic manipulation, tactile sensing is less exploited; mainly due to the complexity of the time series provided by tactile sensors. In this work, we propose a method for assessing grasp stability using tactile sensing. More specifically, we propose a methodology to extract task-relevant features and design efficient classifiers to detect object slippage with respect to individual fingertips. We compare two classification models: support vector machine and logistic regression. We use highly sensitive Uskin tactile sensors mounted on an Allegro hand to test and validate our method. Our results demonstrate that the proposed method is effective in slippage detection in an online fashion.Comment: IEEE International Conference on Development and Learning 2023 (ICDL), Nov 2023, Macau, Chin

Methods and Sensors for Slip Detection in Robotics: A Survey

The perception of slip is one of the distinctive abilities of human tactile sensing. The sense of touch allows recognizing a wide set of properties of a grasped object, such as shape, weight and dimension. Based on such properties, the applied force can be accordingly regulated avoiding slip of the grasped object. Despite the great importance of tactile sensing for humans, mechatronic hands (robotic manipulators, prosthetic hands etc.) are rarely endowed with tactile feedback. The necessity to grasp objects relying on robust slip prevention algorithms is not yet corresponded in existing artificial manipulators, which are relegated to structured environments then. Numerous approaches regarding the problem of slip detection and correction have been developed especially in the last decade, resorting to a number of sensor typologies. However, no impact on the industrial market has been achieved. This paper reviews the sensors and methods so far proposed for slip prevention in artificial tactile perception, starting from more classical techniques until the latest solutions tested on robotic systems. The strengths and weaknesses of each described technique are discussed, also in relation to the sensing technologies employed. The result is a summary exploring the whole state of art and providing a perspective towards the future research directions in the sector

Touching on elements for a non-invasive sensory feedback system for use in a prosthetic hand

Hand amputation results in the loss of motor and sensory functions, impacting activities of daily life and quality of life. Commercially available prosthetic hands restore the motor function but lack sensory feedback, which is crucial to receive information about the prosthesis state in real-time when interacting with the external environment. As a supplement to the missing sensory feedback, the amputee needs to rely on visual and audio cues to operate the prosthetic hand, which can be mentally demanding. This thesis revolves around finding potential solutions to contribute to an intuitive non-invasive sensory feedback system that could be cognitively less burdensome and enhance the sense of embodiment (the feeling that an artificial limb belongs to one’s own body), increasing acceptance of wearing a prosthesis.A sensory feedback system contains sensors to detect signals applied to the prosthetics. The signals are encoded via signal processing to resemble the detected sensation delivered by actuators on the skin. There is a challenge in implementing commercial sensors in a prosthetic finger. Due to the prosthetic finger’s curvature and the fact that some prosthetic hands use a covering rubber glove, the sensor response would be inaccurate. This thesis shows that a pneumatic touch sensor integrated into a rubber glove eliminates these errors. This sensor provides a consistent reading independent of the incident angle of stimulus, has a sensitivity of 0.82 kPa/N, a hysteresis error of 2.39±0.17%, and a linearity error of 2.95±0.40%.For intuitive tactile stimulation, it has been suggested that the feedback stimulus should be modality-matched with the intention to provide a sensation that can be easily associated with the real touch on the prosthetic hand, e.g., pressure on the prosthetic finger should provide pressure on the residual limb. A stimulus should also be spatially matched (e.g., position, size, and shape). Electrotactile stimulation has the ability to provide various sensations due to it having several adjustable parameters. Therefore, this type of stimulus is a good candidate for discrimination of textures. A microphone can detect texture-elicited vibrations to be processed, and by varying, e.g., the median frequency of the electrical stimulation, the signal can be presented on the skin. Participants in a study using electrotactile feedback showed a median accuracy of 85% in differentiating between four textures.During active exploration, electrotactile and vibrotactile feedback provide spatially matched modality stimulations, providing continuous feedback and providing a displaced sensation or a sensation dispatched on a larger area. Evaluating commonly used stimulation modalities using the Rubber Hand Illusion, modalities which resemble the intended sensation provide a more vivid illusion of ownership for the rubber hand.For a potentially more intuitive sensory feedback, the stimulation can be somatotopically matched, where the stimulus is experienced as being applied on a site corresponding to their missing hand. This is possible for amputees who experience referred sensation on their residual stump. However, not all amputees experience referred sensations. Nonetheless, after a structured training period, it is possible to learn to associate touch with specific fingers, and the effect persisted after two weeks. This effect was evaluated on participants with intact limbs, so it remains to evaluate this effect for amputees.In conclusion, this thesis proposes suggestions on sensory feedback systems that could be helpful in future prosthetic hands to (1) reduce their complexity and (2) enhance the sense of body ownership to enhance the overall sense of embodiment as an addition to an intuitive control system

Slippage detection with piezoresistive tactile sensors

One of the crucial actions to be performed during a grasping task is to avoid slippage. The human hand can rapidly correct applied forces and prevent a grasped object from falling, thanks to its advanced tactile sensing. The same capability is hard to reproduce in artificial systems, such as robotic or prosthetic hands, where sensory motor coordination for force and slippage control is very limited. In this paper, a novel algorithm for slippage detection is presented. Based on fast, easy-to-perform processing, the proposed algorithm generates an ON/OFF signal relating to the presence/absence of slippage. The method can be applied either on the raw output of a force sensor or to its calibrated force signal, and yields comparable results if applied to both normal or tangential components. A biomimetic fingertip that integrates piezoresistive MEMS sensors was employed for evaluating the method performance. Each sensor had four units, thus providing 16 mono-axial signals for the analysis. A mechatronic platform was used to produce relative movement between the finger and the test surfaces (tactile stimuli). Three surfaces with submillimetric periods were adopted for the method evaluation, and 10 experimental trials were performed per each surface. Results are illustrated in terms of slippage events detection and of latency between the slippage itself and its onset