Motion Control Module Research Articles

System Design of Three-coordinate Dynamic Synchronous Tester Based on STM32

In this paper, a three-coordinate dynamic synchronous tester system based on STM32 is developed. STM32F103C8T6 chip is used as the control system. The control system mainly consists of three modules: motion control module, magnetic encoder measurement module and displacement data collection module. The STM32 main control controls the three-axis stepper table to move according to the specified instructions, the AS5600 magnetic encoder is used to measure the data of the three-way stepper motor, and the TCA9548A module is used to expand the IIC channel and realize the communication between the STM32 and the host computer, and the data is transmitted to the host computer through serial communication. The test results show that the system meets the needs of the existing domestic industrial level, the cost is moderate, the performance is reliable and the operation is simple, and meets the practical application requirements.

Peripheral cranio-spinal nerve communication for trapezius muscle control using axonal profiling through immunostaining

Accessory nerve (CNXI) has been known to be the primary conduit for motor control of the trapezius, while the supplementary cervical nerves (C3 and C4) are responsible for processing sensory information from muscle. However, the lack of substantial direct evidence has led to these conclusions being regarded as mere speculation. This study used immunostaining (using antibodies against neurofilament 200 for all axons, choline acetyltransferase for cholinergic axons, tyrosine hydroxylase for sympathetic axons, and alpha 3 sodium potassium ATPase for proprioceptive afferent axons) of human samples to verify the functional contributions of nerves. Study highlights the pivotal role of C3 and C4 in regulating precise movements of trapezius, contributing to motor control, proprioceptive feedback, and sympathetic modulation. CNXI is composed primarily of somatic efferent fibers, with significant numbers of sympathetic or sensory fibers. Furthermore, C3-4 have both cholinergic and non-cholinergic axons, suggesting their involvement in proprioceptive feedback and somatic efferent functions. Although less common, mechanosensors such as nociceptive sensor and sympathetic fibers are also supplied by these cervical nerves. The study demonstrated that these nerves contain motor fibers and significant proprioceptive and sympathetic axons, challenging the long-held notion that CNXI are motor and upper spinal nerves are sensory.

Examining the Effect of Noninvasive Brain Stimulation on Hemispheric Lateralization of Motor Learning During a Functional Fine Motor Task

Abstract Date Presented 03/23/24 This study explores how noninvasive brain stimulation of the left and right posterior parietal cortex influences bilateral fine motor control. Results suggest distinct effects on speed and accuracy to help understand fine motor control modulation. Primary Author and Speaker: Sydney C. Sharp Additional Authors and Speakers: Brooke Dexheimer

Development of motion control function library based on PLCopen specification

The motion control library is a standard set of functional blocks integrated in a programmable integration environment, which is of great significance for the rapid development of reconfigurable Programmable Automation Controllers (PAC). However, due to the encapsulation and concealment of function blocks and the incompatibility between software and hardware, the development efficiency of function blocks is low, which is not conducive to the development of autonomous, controllable PAC. Aiming at the above problems, the methods of function block opening and key technology are studied, and a kind of motion control function library architecture and rapid development method based on the PLCopen specification are proposed. A series of motion control function libraries are developed on domestic PLC software. An experimental platform based on domestic hardware and software was designed to verify the typical motion control function library. Experimental results show that this method can effectively shorten the development cycle and that the developed motion control module can meet the actual control needs.

The role of orexin in Parkinson's disease.

Emerging evidence has implicated the orexin system in non-motor pathogenesis of Parkinson's disease. It has also been suggested the orexin system is involved in the modulation of motor control, further implicating the orexin system in Parkinson's disease. Parkinson's disease is the second most common neurodegenerative disease with millions of people suffering worldwide with motor and non-motor symptoms, significantly affecting their quality of life. Treatments are based solely on symptomatic management and no cure currently exists. The orexin system has the potential to be a treatment target in Parkinson's disease, particularly in the non-motor stage. In this review, the most current evidence on the orexin system in Parkinson's disease and its potential role in motor and non-motor symptoms of the disease is summarized. This review begins with a brief overview of Parkinson's disease, animal models of the disease, and the orexin system. This leads into discussion of the possible roles of orexin neurons in Parkinson's disease and levels of orexin in the cerebral spinal fluid and plasma in Parkinson's disease and animal models of the disease. The role of orexin is then discussed in relation to symptoms of the disease including motor control, sleep, cognitive impairment, psychological behaviors, and the gastrointestinal system. The neuroprotective effects of orexin are also summarized in preclinical models of the disease.

Forelimb muscle activation patterns in American alligators: Insights into the evolution of limb posture and powered flight in archosaurs.

The evolution of archosaurs provides an important context for understanding the mechanisms behind major functional transformations in vertebrates, such as shifts from sprawling to erect limb posture and the acquisition of powered flight. While comparative anatomy and ichnology of extinct archosaurs have offered insights into musculoskeletal and gait changes associated with locomotor transitions, reconstructing the evolution of motor control requires data from extant species. However, the scarcity of electromyography (EMG) data from the forelimb, especially of crocodylians, has hindered understanding of neuromuscular evolution in archosaurs. Here, we present EMG data for nine forelimb muscles from American alligators during terrestrial locomotion. Our aim was to investigate the modulation of motor control across different limb postures and examine variations in motor control across phylogeny and locomotor modes. Among the nine muscles examined, m. pectoralis, the largest forelimb muscle and primary shoulder adductor, exhibited significantly smaller mean EMG amplitudes for steps in which the shoulder was more adducted (i.e., upright). This suggests that using a more adducted limb posture helps to reduce forelimb muscle force and work during stance. As larger alligators use a more adducted shoulder and hip posture, the sprawling to erect postural transition that occurred in the Triassic could be either the cause or consequence of the evolution of larger body size in archosaurs. Comparisons of EMG burst phases among tetrapods revealed that a bird and turtle, which have experienced major musculoskeletal transformations, displayed distinctive burst phases in comparison to those from an alligator and lizard. These results support the notion that major shifts in body plan and locomotor modes among sauropsid lineages were associated with significant changes in muscle activation patterns.

Estimation of Lateral Velocity and Cornering Stiffness in Vehicle Dynamics Based on Multi-Source Information Fusion

<div>To address the challenge of directly measuring essential dynamic parameters of vehicles, this article introduces a multi-source information fusion estimation method. Using the intelligent front camera (IFC) sensor to analyze lane line polynomial information and a kinematic model, the vehicle’s lateral velocity and sideslip angle can be determined without extra sensor expenses. After evaluating the strengths and weaknesses of the two aforementioned lateral velocity estimation techniques, a fusion estimation approach for lateral velocity is proposed. This approach extracts the vehicle’s lateral dynamic characteristics to calculate the fusion allocation coefficient. Subsequently, the outcomes from the two lateral velocity estimation techniques are merged, ensuring rapid convergence under steady-state conditions and precise tracking in dynamic scenarios. In addition, we introduce a tire parameter online adaptive module (TPOAM) to continually update essential tire parameters such as cornering stiffnesses, with its effectiveness demonstrated through DLC and slalom simulation tests. Using a dual extended Kalman filter (DEKF) observer, the article allows for joint estimation of vehicle states and tire parameters. Ultimately, we offer a cost-effective estimation method of vital dynamic vehicle parameters to support the motion control module in autonomous driving.</div>

Participation of glutamic acid in the catecholamines release from the amygdala of rabbits

Glutamic acid (Glu), as the most stimulating neurotransmitter, occurs in almost all structures of the central nervous system (CNS). Especially high concentrations are found in the structures of the motivational system (hypothalamus, hippocampus, amygdala, prefrontal cortex – mPFC) and the motor system (striatum, caudate nucleus, pallidum). Glu is also found in the autonomic nervous system (ANS), as well as in peripheral tissues and organs (in the adrenal glands, especially important in stress; the hypothalamic-pituitary-adrenal axis – HPA axis). Catecholamines (CA), including dopamine (DA), norepinephrine (NE), and/or epinephrine (E), are major neurotransmitters that mediate various CNS functions, such as motor control, cognition, emotion, memory processing, pain, stress, and endocrine modulation. The aim of the study was to investigate the in vitro effect of different concentrations of Glu (5, 50, and 200 μM in a volume of 1 ml of Krebs medium) on CA release from rabbit amygdala sections collected after decapitation of 12-week-old female rabbits. The same piece of tissue was transferred every 30 minutes to successive incubation wells containing Glu in an appropriate dose. The medium collected from the wells after 30, 60, and 90 minutes of incubation was frozen until DA, NE, and E analyses were performed by the RIA method. The results showed that Glu differently affected CA release from the amygdala. Generally, an inhibitory effect of Glu on CA release from the amygdala was observed. It was surprising to find the highest concentration of E in the amygdala compared to NA and even DA.

The dual function of prokinesis in the feeding and locomotor systems of parrots.

Prokinesis, a mode of avian cranial kinesis involving motion between the neurocranium and upper beak, has long been investigated in biomechanical analyses of avian feeding and drinking. However, the modern avian beak is also used for non-feeding functions. Here, we investigate the dual function of prokinesis in the feeding and locomotor systems of the rosy-faced lovebird (Agapornis roseicollis). Lovebirds and other parrots utilize their beak both during feeding and as a third limb during vertical climbing. Thus, we experimentally measured both force-generating potential and movement of the rosy-faced lovebird mandible and maxilla (via prokinetic flexion of the craniofacial hinge) during tripedal climbing and mandibular/maxillary adduction. We found that whereas the maxilla is primarily responsible for generating force during locomotion, the mandible is primarily responsible for generating force during forceful jaw adduction, hinting at a remarkable capacity to alter prokinetic function with differing neuromuscular control. The ability of the prokinetic apparatus to perform functions with competing optimality criteria via modulation of motor control illustrates the functional plasticity of the avian cranial kinesis and sheds new light on the adaptive significance of cranial mobility.

Simulation Of Startup Speed of DC Motor Using PI And PID Control

Proportional-Integral (PI) control and Proportional-Integral-Derivative (PID) control have found widespread application across various disciplines. This article focuses on the impact of PI and PID control on the startup speed of the Direct-Current (DC) motor. By setting up a simulation circuit and simulation module, the gain parameters of the control module are adjusted to obtain different output results. The simulation circuit will involve the DC motor, the control module, and the desired speed input. By adjusting the gain parameters of the control module, the behavior of the motor's startup speed can be simulated and observed. For PI control, increasing both the proportional gain and the integral gain proportionally can lead to shorter settling time and smaller overshoot in the output response. For PID control, increasing the derivative gain can significantly reduce the settling time without causing a significant change in the overshoot. When comparing PI and PID controllers, the addition of the derivative term can improve the output performance. By simulating different control modules and adjusting the gains, it is possible to qualitatively identify controllers with better control performance and more suitable gain parameters. This provides insights for the future design and application of DC motor control modules.

Staged Embankment Construction in Geotechnical Centrifuges

Abstract This study develops a novel apparatus to simulate the staged, automatic construction of embankments in geotechnical centrifuges with improved measurement accuracy. Modular test equipment was designed to incorporate the functionality of controllable and precise sand release; its structural components include a box-like sand storage module, a push-pull sand release module, and a stepper motor control module. Emphasis was placed on the design of segmented deflectors, the angles of which were derived with rigorous mathematical analysis to mitigate the Coriolis effect on falling sand. Calibration tests demonstrate that the post-construction embankment geometry approximates its target shape with a relative error of 0.72 to 7.37 % in different construction phases at an acceleration of 60 g. A trial was conducted on a staged embankment over the deformable ground, and the displacement of this system was monitored and characterized by tracking reflective marker technology. The results indicate that the proposed method is effective and reflects real-life situations.

Artistic Robotic Arm: Drawing Portraits on Physical Canvas under 80 Seconds.

In recent years, the field of robotic portrait drawing has garnered considerable interest, as evidenced by the growing number of researchers focusing on either the speed or quality of the output drawing. However, the pursuit of either speed or quality alone has resulted in a trade-off between the two objectives. Therefore, in this paper, we propose a new approach that combines both objectives by leveraging advanced machine learning techniques and a variable line width Chinese calligraphy pen. Our proposed system emulates the human drawing process, which entails planning the sketch and creating it on the canvas, thus providing a realistic and high-quality output. One of the main challenges in portrait drawing is preserving the facial features, such as the eyes, mouth, nose, and hair, which are crucial for capturing the essence of a person. To overcome this challenge, we employ CycleGAN, a powerful technique that retains important facial details while transferring the visualized sketch onto the canvas. Moreover, we introduce the Drawing Motion Generation and Robot Motion Control Modules to transfer the visualized sketch onto a physical canvas. These modules enable our system to create high-quality portraits within seconds, surpassing existing methods in terms of both time efficiency and detail quality. Our proposed system was evaluated through extensive real-life experiments and showcased at the RoboWorld 2022 exhibition. During the exhibition, our system drew portraits of more than 40 visitors, yielding a survey outcome with a satisfaction rate of 95%. This result indicates the effectiveness of our approach in creating high-quality portraits that are not only visually pleasing but also accurate.

Speed Control of Induction Motor by Using Voice Recognition Using Bluetooth

The project's goal is to develop a voice recognition and Bluetooth communication-based system for managing an induction motor's speed. The system is made up of two primary components: the speech recognition module, which is in charge of understanding user voice instructions, and the motor control module, which regulates to response to user voice commands. A speech recognition algorithm processes the user's vocal commands after being captured by the voice recognition module's microphone. control module receives the commands from the algorithm via Bluetooth communication. PWM method is used by the module to adjust the speed of induction after receiving commands. Without the use of physical buttons or switches, voice recognition technology offers customers a simple and practical way to adjust the motor's speed. The study shows that voice recognition technology and Bluetooth connectivity may be used to regulate the speed of induction motors, providing a practical and user-friendly solution for a variety of applications. Key Word: Induction motor, voice recognition, pulse-width modulation.

Robust nonlinear path-tracking control of vector-propelled AUVs in complex sea conditions

Aiming to address the trajectory tracking problem of vector propulsion autonomous underwater vehicles (vector AUVs) under complex sea conditions, this paper proposes a dynamic control system based on vector propulsion (DS-Vector). The vector AUV has the vector characteristics of four tilt thrusters and is highly maneuverable. Based on the approximate kinematics and dynamics equations of the vector AUV under the action of current disturbance obtained through analysis, the proposed DS-Vector has a motion control module and force distribution control module. The motion control module adopts the control method by combining the nonsingular fast terminal sliding mode control based on an adaptive disturbance observer (NTSMC-ADO) and PID control law, while the force distribution control module selects the least square (LS) method. The effectiveness and robustness of the proposed DS-Vector are verified in an underwater visual simulation environment. To verify the superiority of the NTSMC-ADO designed in this paper, three other advanced control laws are used in DS-Vector for comparison. The results show that NTSMC-ADO has better anticurrent interference and better position tracking control response and is more robust than the other three advanced control laws.

Development of Autonomous Driving and Motion Control System for a Patient Transfer Robot

In this study, an autonomous driving system of a patient-transfer robot is developed. The developed autonomous driving system has a path-planning module and a motion-control module. Since the developed autonomous driving system is applied to medical robots, such as patient-transfer robots, the main purpose of this study is to generate an optimal path for the robot’s movement and to ensure the patient on board moves comfortably in the PTR. In particular, for the patient’s comfortable movement, a lower controller is needed to minimize the sway angle of the patient. In this paper, we propose a hybrid path-planning algorithm that combines the A-STAR algorithm as a global path-planning method and the AHP (Analytic Hierarchy Process)-based path-planning algorithm as a local path-planning method. In addition, model-based controllers are designed to move patient-transport robots along planned paths. In particular, the LQR controller with the Kalman filter is designed to be robust to the uncertainty and disturbance of the model including the patient. The optimal path generation and patient shaking angle reduction performance of the proposed autonomous driving system have been demonstrated via a simulation on a map that mimics a hospital environment.

Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot.

The aim of this work is to propose bio-inspired neural networks for decision-making mechanisms and modulation of motor control of an automaton. In this work, we have adapted and applied cortical synaptic circuits, such as short-term memory circuits, winner-take-all (WTA) class competitive neural networks, modulation neural networks, and nonlinear oscillation circuits, in order to make the automaton able to avoid obstacles and explore simulated and real environments. The performance achieved by using biologically inspired neural networks to solve the task at hand is similar to that of several works mentioned in the specialized literature. Furthermore, this work contributed to bridging the fields of computational neuroscience and robotics.

Continuously-deformable and stiffness-tunable soft manipulator achieving unmanned COVID-19 pandemic sampling

In recent years, COVID-19 has spread across the whole world, and manpowered collection of pharyngeal samples undoubtedly increases the possibility of cross-infections. In this article, based on our previous fabricated soft manipulator (Cell Reports Physical Science, 2021, 2, 100600), we performed the COVID-19 sampling on real human volunteers by exploiting a pre-programmed unmanned system. The unmanned sampling system mainly includes a soft manipulator and a rigid motion platform, which are adjusted by pneumatic control box and the motor control modules, respectively. Drawn on the lead-through teaching method, the unmanned sampling of COVID-19 is realized by recording the applied pressure in soft manipulator and the feed motion of rigid platform. This research provides a potential approach for unmanned COVID-19 sampling, solving the risk of cross-infection during manual collection.

GIN: Graph-Based Interaction-Aware Constraint Policy Optimization for Autonomous Driving

Applying reinforcement learning to autonomous driving entails particular challenges, primarily due to dynamically changing traffic flows. To address such challenges, it is necessary to quickly determine response strategies to the changing intentions of surrounding vehicles. This letter proposes a new policy optimization method for safe driving using graph-based interaction-aware constraints. In this framework, the motion prediction and control modules are trained simultaneously while sharing a latent representation that contains a social context. To reflect social interactions, we illustrate the movements of agents in graph form and filter the features with the graph convolution networks. This helps preserve the spatiotemporal locality of adjacent nodes. Furthermore, we create feedback loops to combine these two modules effectively. As a result, this approach encourages the learned controller to be safe from dynamic risks and renders the motion prediction robust to abnormal movements. In the experiment, we set up a navigation scenario comprising various situations with CARLA, an urban driving simulator. The experiments show state-of-the-art performance on navigation strategy and motion prediction compared to the baselines.

Design of intelligent robots for tourism management service based on green computing.

The modular intelligent robot platform has important application prospects in the field of tourism management services. Based on the intelligent robot in the scenic area, this paper constructs a partial differential analysis system for tourism management services, and adopts the modular design method to complete the hardware design of the intelligent robot system. Through system analysis, the whole system is divided into 5 major modules, including core control module, power supply module, motor control module, sensor measurement module, wireless sensor network module, to solve the problem of quantification of tourism management services. In the simulation process, the hardware development of wireless sensor network node is carried out based on MSP430F169 microcontroller and CC2420 radio frequency wireless communication chip, and the corresponding physical layer and MAC (Media Access Control) layer data definition and data definition of IEEE802.15.4 protocol are completed for software implementation, and data transmission and networking verification. The experimental results show that the encoder resolution is 1024P/R, the power supply voltage is DC5V5%, and the maximum response frequency is 100 kHz. The algorithm designed by MATLAB software can avoid the existing shortcomings and meet the real-time requirements of the system, which significantly improves the sensitivity and robustness of the intelligent robot.

Unmanned Driving Technology in Coal Mine Based on Semantic Information Method

Aiming at the transportation scheduling problem of unmanned trucks in open-pit mines, an optimization model for transportation scheduling of unmanned trucks in open-pit mines is established, taking the minimum sum of fuel cost, fixed start-up cost, fault maintenance cost and network base station construction and maintenance cost as the objective function, and taking mining amount, crushing amount in crushing field, truck number and truck transportation work as the bundle reduction conditions. By adjusting the position of the encapsulated individual and the optimal encapsulated individual through the parameter position adaptive updating mechanism, the search range of the solution space can be enlarged, so that the algorithm can jump out of the local optimum. This paper analyzes the influence of vehicle clearance on coordinated traffic at intersections under clearance theory, and puts forward the minimum vehicle clearance to meet coordinated traffic. Generate trajectories with behavioral semantics through hierarchical online selection of primitives; Based on the model predictive control algorithm, the motion control module fully considers the execution ability, tracking deviation and control stability of the platform drive motor, and updates the weight coefficient of the control objective function in real time with the help of the semantic attributes of the behavioral motion primitives given by the motion planning, so as to reduce the lateral error, heading error and speed error of the trajectory tracking. Finally, a real vehicle is verified by a medium-sized hybrid unmanned crawler platform, which proves that the proposed intersection coordinated traffic model is feasible in theory, reflecting that the traffic density is a factor that affects the transportation efficiency. Under the condition of meeting the production requirements, reduce the intersection conflict and improve the traffic capacity of the intersection by adopting large-load unmanned mine trucks as much as possible, reducing the number of unmanned mine trucks and the interference between equipment.