International Journal of Robotics and Automation Technology

Design and Simulation Analysis of Robot-Assisted Plate Internal Fixation Device for Lower Limb Fractures

Yongqiang Zhou — 2023-01-24

Abstract: Internal fixation with steel plates is a common method for the therapy of lower limb fractures. Due to the disadvantages of traditional surgical methods such as high trauma and complications, the application of robots for minimally invasive surgery has become a popular research direction. In this article, we have designed and simulated the overall structure of a steel plate internal fixation device used in conjunction with a robotic arm. Firstly, a finite element model of cortical bone drilling was established based on ABAQUS to obtain the torque and axial force when drilling the cortical bone. Then a virtual prototype of the robot-assisted lower limb bone fracture plate internal fixation device was designed, and the outer shell, drilling mechanism, nail placement mechanism, nail supply mechanism, drive mechanism, and guide sleeve were refined based on the overall mechanical structure of the device, so that the device could continuously perform drilling and nail placement. Afterward, the device was simulated based on ADAMS, and the motion curves of each component were obtained to verify the feasibility of the device’s working principle and to validate the performance of the servo. Finally, the modal analysis of the device was carried out with the finite element software ABAQUS, and the modal parameters of the first six orders were obtained, which were compared with the operating frequencies of the motor and the servo to verify that the device is not easy to resonate during normal operation, and the static strength checks of the key components were carried out, and the stress and deformation clouds and upper limits of flexural values of the components were obtained, which proved that the structure has stability.

Data–Driven Wake Steering Control for a Simulated Wind Farm Model

Silvio Simani — 2023-04-07

Abstract: Upstream wind turbines yaw to divert their wakes away from downstream turbines, increasing the power produced. Nevertheless, the majority of wake steering techniques rely on offline lookup tables that translate a set of parameters, including wind speed and direction, to yaw angles for each turbine in a farm. These charts assume that every turbine is working well, however they may not be very accurate if one or more turbines are not producing their rated power due to low wind speed, malfunctions, scheduled maintenance, or emergency maintenance. This study provides an intelligent wake steering technique that, when calculating yaw angles, responds to the actual operating conditions of the turbine. A neural network is trained live to determine yaw angles from operating conditions, including turbine status, using a hybrid model and a learning-based method, i.e. an active control. The proposed control solution does not need to solve optimization problems for each combination of the turbines’ non-optimal working conditions in a farm; instead, the integration of learning strategy in the control design enables the creation of an active control scheme, in contrast to purely model-based approaches that use lookup tables provided by the wind turbine manufacturer or generated offline. The suggested methodology does not necessitate a substantial amount of training samples, unlike purely learning-based approaches like model-free reinforcement learning. In actuality, by taking use of the model during back propagation, the suggested approach learns more from each sample. Based on the flow redirection and induction in the steady state code, results are reported for both normal (nominal) wake steering with all turbines operating as well as defective conditions. It is a free tool for optimizing wind farms that The National Renewable Energy Laboratory (USA) offers. These yaw angles are contrasted and checked with those discovered through the resolution of an optimization issue. Active wake steering is made possible by the suggested solution, which employs a hybrid model and learning-based methodology, through sample efficient training and quick online evaluation. Finally, a hardware-in-the-loop test-bed is taken into consideration for assessing and confirming the performance of the suggested solutions in a more practical setting.

Virtual Sensor Design for Replacement the Faulty Physical Sensors

Alexey Zhirabok — 2023-06-24

Abstract: The paper considers the problem of virtual sensor design for nonlinear dynamic systems with non-smooth nonlinearities described by continuous-time models for faulty physical sensor replacement. It is assumed that to solve the problem, the system is equipped by diagnostic system allowing detecting and isolating the faulty sensor. For every such a sensor, the virtual sensor generating estimate replacing the faulty sensor is designed. To solve the problem, so-called logic-dynamic approach is used which does not guarantee optimal solution but uses only methods of linear algebra to solve the problem for systems with non-smooth nonlinearities. The virtual sensor can be designed in the identification canonical form or Jordan canonical form. The advantage of the first form is a standard procedure of the virtual sensor design while Jordan form allows obtaining a simpler solution. The relations allowing designing the virtual sensor both in identification and in Jordan canonical form are derived.

Design and Analysis of a High-Precision Horizontal Machine Tools

Tzu-Chi Chan — 2023-07-05

Abstract: The horizontal machine tool has an automatic exchange table, which can be combined with a flexible manufacturing system for automatic processing and production. Therefore, it requires higher performance stability than other machines. This study analyzes the static and dynamic characteristics of a horizontal machine tool structure. The finite element analysis (FEA) method is generally used to analyze the whole machine structure and improve the deformation and resonance of the horizontal machine tool. In this study, FEA was applied to the design process of the machine tool, including static deformation analysis, modal analysis, transient analysis, and harmonic analysis of the machine. The deformation of the whole machine due to acceleration of gravity and cutting force was analyzed. The modal shapes generated by the first and third modes directly affected the machining process of the machine tool. To further analyze the influence of vibration signal processing on processing quality, transient response analysis was carried out on the effect of axial cutting force during machining. Spectrum analysis of the machine was also carried out. This study is expected to help the structural design of a horizontal machine tool to improve the dynamic characteristics and stability of the horizontal machining system.

A Review on Variation Modeling of Aircraft Assembly

Yifan Zhang — 2023-09-10

Abstract: Purpose; The purpose of this paper is to provide a state-of-art review on variation modeling and propagation in aircraft assembly based on process-oriented strategy. And the main focus is on classifying and delineating different approaches, methods, and techniques with critical appraisals of their theories, applications, and limitations, based on which future research directions and corresponding methodologies are proposed.

Design/methodology/approach; To facilitate understanding of the background, this paper starts with a brief description of aircraft assembly. Afterwards, this paper presents a comprehensive review of practical solutions in aircraft variation modeling. Their characteristics are summarized, which serves as a basis for the discussion of deviation control strategies. Thereafter, the possible trends are discussed to facilitate assembly quality control in future research.

Opposition-Based Learning Equilibrium Optimizer with Application in Mobile Robot Path Planning

Zongshan Wang — 2023-09-22

Abstract: The objective of mobile robot path planning (MRPP) is to devise the shortest obstacle-free path for autonomous mobile robots based on a given terrain. Numerous MRPP methods have been extensively researched. This paper presents a novel approach called Opposition-based Learning Equilibrium Optimizer (OEO) for generating smooth paths for mobile robots. The fundamental idea behind OEO is to introduce an opposition-based learning mechanism while maintaining the overall framework of the basic EO algorithm. This modification alleviates the susceptibility of the basic EO algorithm to local optima. The OEO algorithm is employed to provide smooth paths for autonomous mobile robots, and the results are compared with several classical metaheuristic algorithms. Comparative analysis across different environments demonstrates that the proposed OEO-based path planning method consistently yields the shortest and most collision-free paths with superior stability.

Design and Experiment of a Reconfigurable Bypass Downlink Surface Equipment for Transmitting the Surface Information to Deep Well

Jiafeng Wu — 2023-11-30

Abstract: In order to achieve the transmission of the control information from the surface to the downhole in the deep well during drilling, a design method of a new downlink surface equipment for generating negative pulse signals is presented in this paper. The equipment uses adjustable throttle control valve and pressure drop module (PDM) to realize bypass flow control. The PDM uses multistage variable nozzles to reduce drilling fluid pressure and meet drilling requirements under different pressure and flow rates. Design theory of the downlink surface equipment is established, and a specific design instance is given according to actual drilling conditions. Both laboratory and field experimental results verify the correctness of the proposed design method. The research results show that the design equipment can meet the needs of the transmission of the surface information, and the downlink transmission rate can reach at least one-bit data per 8 sec. The maximum pressure drop is realized by the PDM and the pressure drop at the control valve will be reduced according to drilling demand, the fluid velocity in the equipment is reduced as much as possible, the erosion of the drilling fluid to the equipment is reduced, and the service life can be improved effectively.

Research on Force Interaction Devices Specialized for Blind Guidance Robot

Bin Hong — 2023-12-02

Abstract: As a new type of human-computer interaction, physical human-robot interaction is very common in guide robots and is the mainstream of future development. However, the force interaction device is hard to choose according to actual application requirements. In this paper, we compared the force transmission characteristics of three interaction mediums: rigid rod, spring-damping, and cable. The result shows that the rigid rod will bring a force impact on blind users when the robot’s motion state switches, while the spring-damper can not perform well in its response and stability. In contrast, the cable is more suitable in this area for its fast response and stability, moreover, it does not impose a dramatic impact when imposing an excitation force.

Design of Crop Irrigation Decision-Making System Based on ZigBee Technology

Qiang Sheng — 2023-12-02

Abstract: To promote the high-quality development of agriculture, meet the needs of agricultural products grown in greenhouses, and achieve precise monitoring of greenhouse plants, a small greenhouse micro-environment multi-parameter monitoring system was designed and implemented. The system consists of three parts: a monitoring node, a gateway node, and a remote management platform. The monitoring node used the ESP32 microcontroller as the main control chip, combined ZigBee technology, and embedded different sensors to complete the collection and transmission of environmental parameters. In the gateway node, the 4G Data Transfer Unit module was used as the carrier, and the communication protocol was used to realize data communication between the monitoring terminal and the gateway. The remote management platform was based on the PyCharm development platform. It used the PyQt5 graphical user interface (GUI) toolkit to complete the design of the host computer monitoring platform, establish a database, and realize the storage and analysis of environmental parameters. The remote management platform embedded the crop reference evapotranspiration, online calculation model, to provide irrigation decisions for greenhouse crop management and improve the applicability and accuracy of irrigation decisions. After the experimental test platform was built to test the system communication distance, communication reliability, control reliability, and data reliability, the small greenhouse micro-environment multi-parameter monitoring system designed in this paper can operate stably for a long time. Its functions meet the expected requirements and are in line with modern requirements for multi-parameter monitoring of smart greenhouses.

MIG-Assisted Kernel-Enabled Robot (MAKER) Arm for Seamless Automobile Maintenance and Service

Hwang-Cheng Wang — 2023-12-15

Abstract: There is a definitive increase of excellence in the field of robotic automation, with automated vehicles that can drive people anywhere to automated robots that can perform high-risk surgeries remotely. Robotic automation was initiated as an industrial-grade asset capable of performing complex tasks and replacing humans limited by fatigue. With the advent and rise of Industry Revolution 4.0 (IR 4.0), in the modern world, one of the major markets that IR 4.0 occupies is the automobile industry. The automobile industry heavily employs robotic technology for vehicle manufacturing and assembly, yet post-sale servicing and maintenance remain predominantly manual. This discrepancy results in a gap in the efficient and timely maintenance of vehicles once they’re in the hands of customers. According to a report of Allied Market Research [1], the expected Compound Annual Growth Rate (CAGR) of the global automobile repair and service market from 2022 - 2031 is expected at 7.6%, corresponding to 1,656.21 billion US dollars by 2031. This establishes the scale of the market that the proposed solution is going to be primarily based on. This paper proposes a MIG-based solution for providing welding service to damaged and sheared automobiles, thus reducing the stated discrepancy. The proposed solution creates a kernel environment where the twin-headed robotic arm can assess its surroundings and perform appropriate action from its operation pool using Reinforcement Learning and Machine Learning. The twin-headed robotic arm holds a torch and lead (Al) on the heads to perform the desired operations. This innovative approach is equipped with advanced sensors and programming to accurately detect, diagnose, and service vehicles by leveraging On Board Diagnostic (OBD) systems. This study delves into the theoretical and technical complexities of building an automated welder that explores the practical application of robotic technology in the automobile aftermarket. Notably, this technology promises improved accuracy, consistency, and timeliness in car maintenance, significantly reducing human error, improving service times, increasing productivity, and inducing economic growth.

MRAC with SMC Applied to Lateral Control of a Fixed-Wing MAV

T. Espinoza- Fraire — 2023-12-18

Abstract: This paper presents a PD control law with adaptive gains with the MIT (Massachusetts Institute Technology) rule with different sliding modes; that is, the MIT rule has been designed with is known in the literature with first order sliding mode, second order sliding mode and high order sliding mode (HOSM) to obtain a better gain scheduling taking advantage the sliding modes techniques-the PD control law with adaptive gains that is designed for the lateral dynamics of a fixed-wing MAV. To apply the methodology of the model reference adaptive control (MRAC), sometimes called model reference adaptive system (MRAS), to the adaptive gains of the PD control, a sliding manifold is proposed considering the output of the lateral dynamics and with the output of the reference model.

Linear Active Disturbance Rejection Lateral Controller for Unmanned All-Terrain Vehicle

Dequan Zeng — 2023-12-20

Abstract: To address the disturbance of model uncertainty, a linear active disturbance rejection controller (LADRC) was designed for robust lateral control of unmanned all-terrain vehicle. In terms of relative motion of target node and current state, first-order lateral tracking model is established. According to the developed model, linear tracking differentiator (LTD), linear extended state observer (LESO) and linear state error feedback (LSEF) are designed in turn. LESO could observe the uncertainty of system and LSEF could compensate the uncertainty to make system robust. In order to verify the effectiveness, two typical scenarios, circle and double lane tracking, were designed for test. And the uncertainties of wheelbase and steering ratio were considered. Results illustrate that the designed LADRC can stably control the unmanned all-terrain vehicle tracking reference trajectory under both scenarios and has the advantages of small tracking error and small overshoot compared with the conventional pure tracking methods.

Research on Semantic Segmentation of Fish-Eye Images for Autonomous Driving

Hongtao Huang — 2023-12-27

Abstract: Fisheye cameras, valued for their wide field of view, play a crucial role in perceiving the surrounding environment of vehicles. However, there is a lack of specific research addressing the processing of significant distortion features in segmenting fish-eye images. Additionally, fish-eye images for autonomous driving face the challenge of few datasets, potentially causing over fitting and hindering the model's generalization ability.

Based on the semantic segmentation task, a method for transforming normal images into fish-eye images is proposed, which expands the fish-eye image dataset. By employing the Transformer network and the Across Feature Map Attention, the segmentation performance is further improved, achieving a 55.6% mIOU on Woodscape. Additionally, leveraging the concept of knowledge distillation, the network ensures a strong generalization based on dual-domain learning without compromising performance on Woodscape (54% mIOU).

Finite Horizon Memory Control of Networked Systems Using Chain-like Lyapunov Function

Liming Liu — 2023-12-29

Abstract: This paper proposes a novel finite horizon memory control (FHMC) design framework for networked systems by using input delay approach. A chain-like input delay model is established to characterize the networked control system (NCS) under memory control architecture in order to make full use of historic sampled-data. Based on the proposed chain-like delay model, the corresponding chain-like Lyapunov-Krasovskii function, which records the historic sampling information of NCS, is well constructed for facilitating further analysis and synthesis of the proposed FHMC scheme. Both state feedback controllers and static output feedback controllers are derived by solving LMIs (Linear matrix inequalities). The proposed FHMC scheme is skilled in improving control performance of networked systems. Simulations show the effectiveness of the presented FHMC scheme.