Robot Prototype Research Articles

A Multi-Terrain Robot Prototype With Archimedean Screw Actuators: Design, Realization, Modeling, and Control

A Multi-Terrain Robot Prototype With Archimedean Screw Actuators: Design, Realization, Modeling, and Control

Research on control strategy of pneumatic soft bionic robot based on improved CPG.

To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic soft bionic robot based on the improved Central Pattern Generator (CPG) is proposed. According to the structure and motion characteristics of the robot, a two-layer neural network topology model for the robot is constructed by coupling 22 Hopfield neuron nonlinear oscillators. Then, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), the membership functions are offline learned and trained to construct the CPG-ANFIS-PID motion control strategy for the robot. Through simulation research on the impact of CPG-ANFIS-PID input parameters on the swimming performance of the robot, it is verified that the control strategy can quickly respond to input parameter changes between different swimming modes, and stably output smooth and continuous dynamic position signals, which has certain advantages. Then, the motion performance of the robot prototype is analyzed experimentally and compared with the simulation results. The results show that the CPG-ANFIS-PID motion control strategy can output coupled waveform signals stably, and control the executing mechanisms of the pneumatic soft bionic robot to achieve biological rhythms motion propulsion waveforms, confirming that the control strategy has accuracy and anti-interference characteristics, and enable the robot have certain maneuverability, flexibility, and environmental adaptability. The significance of this work lies in establishing a CPG-ANFIS-PID control strategy applicable to pneumatic soft bionic robot and proposing a rhythmic motion control method applicable to pneumatic soft bionic robot.

Prototype of a watering autonomous mobile robot for mini greenhouse with manipulator and computer vision

The development of a watering autonomous mobile robot capable of performing intellectual labor functions in place of humans is a pressing task in the fields of robotics and bioinformatics. These robots can be widely utilized in precision agriculture to conserve resources, particularly in the area of optimal plant irrigation. In the context of global urbanization, this study is dedicated to the development of a watering autonomous mobile robot for mini greenhouses. This robot is integrated with microelectronics and micro-automation systems. A prototype robot equipped with a manipulator and computer vision system was created. The developed irrigation schedule and planting methodology enable efficient resource utilization, increased crop yield, and reduced labor costs. Such an approach holds significant practical value for urban agriculture.

Enhancing Precision of Crop Farming towards Smart Cities: An Application of Artificial Intelligence

Water sustainability will be scarce in the coming decades because of global warming, an alarming situation for irrigation systems. The key requirement for crop production is water, and it also needs to fulfill the requirements of the ever-increasing population around the globe. The changing climate significantly impacts agriculture production due to the extreme weather conditions that prevail in various regions. Since urbanization is increasing worldwide, smart cities must find innovative ways to grow food sustainably within built environments. This paper explores how precision agriculture powered by artificial intelligence (AI) can transform crop farms (CF) to enhance food security, nutrition, and environmental sustainability. We developed a robotic CF prototype that uses deep reinforcement learning to optimize seeding, watering, and crop maintenance in response to real-time sensor data. The system was tested in a simulated CF setting and benchmarked. The results revealed a 26% increase in crop yield, a 41% reduction in water utilization, and a 33% decrease in chemical use. We employed AI-enabled precision farming to improve agriculture’s efficiency, sustainability, and productivity within smart cities. The widespread adoption of such technologies makes food supplies resilient, reduces land, and minimizes agriculture’s environmental footprint. This study also qualitatively assessed the broader implications of AI-enabled precision farming. Interviews with farmers and stakeholders were conducted, which revealed the benefits of the proposed approach. The multidimensional impacts of precision crop farming beyond measurable outcomes emphasize its potential to foster social cohesion and well-being in urban communities.

The potential of using 3D printing in the manufacture of mini hydraulic systems

The work is devoted to an analytical engineering study of the practicality of using 3D printing for the manufacture of hydraulic components, in order to solve the problems associated with weight, size and complexity inherent in traditional hydraulic elements. The research aims to demonstrate the feasibility of using 3D printing to achieve simplified design and increased efficiency. The work presents samples of hydraulic elements printed on a 3D printer, which reflects the practical feasibility of this approach. A simple and practical design methodology is proposed for two key components of a typical hydraulic system, namely, a hydraulic cylinder and a directional servo-valve, which allows hydraulic actuators to be controlled using any programmable microcontroller. A distinctive feature of this approach is the emphasis on the principles of compact design, which facilitates the integration of many parts into single, multifunctional part. In addition, the use of lightweight materials in 3D printing helps reduce the overall weight of hydraulic components. The proposed method also allows the integration of various hydraulic elements into a single integral structure printed on a 3D printer, offering a pragmatic solution to the size and complexity issues associated with traditional metal hydraulic systems. The scope of this innovative approach extends to the creation of prototypes of hydraulic and pneumatic robots, as well as devices that require compactness, precision and adaptability. This methodology is promising for implementation in the field of robotics, especially for tasks where space and weight constraints are critical factors.

Toward Bionic Arthroscopy: A Comprehensive Perspective of Continuum Robotics Principles and Prototypes for the Inception of Arthroscopic Surgery Robots

In this study, an innovative exploration of leveraging bionics and continuum robotics principles to develop a novel solution for arthroscopic surgery is embarked on. Inspired by the flexibility and adaptability of organisms like snakes and octopuses, the continuum robot concept aims to address the inherent challenges in traditional arthroscopy, including lower precision, manual tremors, and long surgeon learning curves. The implementation of these principles in the human body, however, faces significant obstacles, particularly achieving high‐performance motion control amid strong nonlinearity and coupling between modules. This research focuses on intelligent integration and enhanced safety in human‐machine interaction, aiming for improved control precision and flexibility in arthroscopic procedures. A thorough literature review of endoscopic continuum robots is conducted, highlighting current advancements in actuation, structure, sensing, and control technologies. The study concludes with an assessment of these technologies, their limitations, and future potential, in light of the unique demands of arthroscopic continuum robots. This comprehensive review bridges bionics and robotics, presenting the opportunities and challenges in applying continuum robotics to arthroscopic surgery. The goal is to encourage further research in this area, contributing to the development of prototype robots that enhance the precision and safety of arthroscopic surgery.

Development of intelligent Municipal Solid waste Sorter for recyclables

Sorting Municipal Solid Waste (MSW) has helped promote the awareness of sustainable development of environment. A robot equipped with an intelligent deep learning (DL) detection algorithm have been proposed to improve the sorting task. But most of the related studies aimed to better the DL algorithms on MSW detection, and few studies integrated the DL algorithms with a robot to identify the dominated factors to Intelligent MSW Sorter (IMSWS). Therefore, this study is to develop IMSWS prototype to better sort MSW, based on the pick-and-place process, and preliminarily evaluate the dominated factors.First, the delta robot prototype was manufactured, and IMSWS was performed with a camera to acquire the RGB image and the height of a MSW in the conveyor belt. The DL algorithm, YOLOv3 or YOLOv4, detected the type and plane location of the MSWs in the conveyor belt. Next, the sequence program transferred the valid MSW data to the delta robot. After the calculation of the absorbed location of the target MSW was made, the arm of this delta robot moved to absorb and then transfer the MSW to the bin. Results showed that the IMSWS prototype could sort the multi-object MSWs in the MSW stream. Both YOLOv3 and YOLOv4 reached high detection accuracy on the MSW image dataset. However, the improvement should be made in the actually moving MSW stream even though the YOLOv4 performed the acceptable detection accuracy. The gripping stability of the arm mainly dominated the performance of IMSWS, and this should be improved first.

A transformable wheel-spoke-paddle hybrid amphibious robot

AbstractThe intricate water-land intermingled nature of wild environments necessitates robots to exhibit multimodal cross-domain mobility capabilities. This paper introduces a novel wheel-spoke-paddle hybrid amphibious robot (WSP-bot) that can operate on flat and rough terrains, water surfaces, and water-land transitional zones. The proposed robot relies on a propulsion mechanism called transformable wheel-spoke-paddle (WSP), which combines the stability of wheeled robots with the obstacle-climbing capability of legged robots, while also providing additional aquatic mobility. The utilization of a crank-slider-based transformation mechanism enables seamless switching between multiple motion modes. An analysis of mode transition and ground motion in spoke mode was conducted, along with an investigation of its obstacle-crossing capability. Simulations were performed for mode transition, ground locomotion, and obstacle-crossing, as well as propulsion of a single WSP module on water. Based on the above work, a prototype robot was manufactured. Prototype tests, including mode transition and mobility tests on land and water surfaces under multimodal states, confirmed the effectiveness of the proposed WSP-bot.

Design and Manufacture of Modular Robotic Cell prototype for application in different production processes

This work presents the design and development of a two-axis robotic cell with a modular and versatile approach for industrial applications. The aim is to enhance efficiency in industrial production through process automation. The modular design allows for future adaptations without significant structural changes. The results demonstrate an increase in production speed, a reduction in errors and waste, and greater consistency in product quality. The investment in this robotic cell is economically justified by its benefits. Safety measures have been implemented to ensure the integrity of operators. Additionally, various applications have been presented, such as the automation of manufacturing processes, painting, and parts organization. This project opens up opportunities for future research, such as process optimization, the integration of artificial intelligence, applications in Industry 4.0, and sustainability

Variable Curvature Modeling Method of Soft Continuum Robots with Constraints

The inherent compliance of continuum robots holds great promise in the fields of soft manipulation and safe human–robot interaction. This compliance reduces the risk of damage to the manipulated object and its surroundings. However, continuum robots possess theoretically infinite degrees of freedom, and this high flexibility usually leads to complex deformations when subjected to external forces and positional constraints. Describing these complex deformations is the main challenge in modeling continuum robots. In this study, we investigated a novel variable curvature modeling method for continuum robots, considering external forces and positional constraints. The robot configuration curve is described using the developed mechanical model, and then the robot is fitted to the curve. A ten-section continuum robot prototype with a length of 1 m was developed in order to validate the model. The feasibility and accuracy of the model were verified by the ability of the robot to reach target points and track complex trajectories with a load. This work was able to serve as a new perspective for the design analysis and motion control of continuum robots.

ROMI: Design and Experimental Evaluation of a Linear Delta Robotic System for High-Precision Applications

In this paper, the design and experimental evaluation of a parallel robotic system based on a linear delta geometry is presented. The design considers the requirements for high-precision applications including workspace, motion resolution, and payload. The entire design process includes robot kinematics, control, and optimization, resulting in the demonstration of a working device. The robot structure offers a versatile and simplified design when compared with state-of-the-art devices being able to be adapted to perform different tasks while keeping the advantages of high precision with reduced complexity. The presented robot prototype was constructed and evaluated experimentally through three proof-of-concept experiments mimicking tasks requiring high motion precision such as microsurgery, semiconductor testing, and optical device alignment. The obtained results in the three experimental scenarios validate that the here-proposed design can achieve an average motion precision of ~3.3 ± 0.3 μm with varying load conditions, thus confirming its potential to be used for high-precision tasks in industrial and medical settings.

Development of a miniature piezoelectric robot combining three unconventional inertial impact modes

A novel miniature piezoelectric robot (MPR) was designed and proposed in this work, in which a unique structural feature is that the robot base is only obtained through a single cuboid block, having good simplicity and compactness. Besides, unlike the slow-fast periodic horizontal deformation of the inertial unit in traditional inertial impact mode, three unconventional (diagonal, jumping, resonant) inertial impact modes (DIIM, JIIM, and RIIM) based on the unique structure of the robot were proposed to achieve the performance improvement in both resolution, single step value, and motion speed. The three working principles were analyzed, and the main geometric parameters were determined by the cooperation of the established model and the finite element method. Then, a robot prototype with a size of 20 mm × 12 mm × 9 mm and a weight of 4.7 g was manufactured, and the motion performance was tested, in which the robot was powered by an external power supply by wires. The results showed that the robot could achieve both high resolution, large single step, and high motion speed successfully by cooperating the three inertial impact modes, including a highest resolution of 0.5 µm under DIIM, a maximum single step of 63.1 µm under JIIM, and a fastest speed of 24.8 mm/s under RIIM. The coordination of these performance could well expand the application scope of MPRs.

In Situ Real-Time Monitoring for Aseptic Drilling: Lessons Learned from the Atacama Rover Astrobiology Drilling Studies Contamination Control Strategy and Implementation and Application to the Icebreaker Mars Life Detection Mission.

In 2019, the Atacama Rover Astrobiology Drilling Studies (ARADS) project field-tested an autonomous rover-mounted robotic drill prototype for a 6-Sol life detection mission to Mars (Icebreaker). ARADS drilled Mars-like materials in the Atacama Desert (Chile), one of the most life-diminished regions on Earth, where mitigating contamination transfer into life-detection instruments becomes critical. Our Contamination Control Strategy and Implementation (CCSI) for the Sample Handling and Transfer System (SHTS) hardware (drill, scoop and funnels) included out-of-simulation protocol testing (out-of-sim) for hardware decontamination and verification during the 6-Sol simulation (in-sim). The most effective five-step decontamination combined safer-to-use sterilants (3%_hydrogen-peroxide-activated 5%_sodium-hypochlorite), and in situ real-time verification by adenosine triphosphate (ATP) and Signs of Life Detector (SOLID) Fluorescence Immunoassay for characterization hardware bioburden and airborne contaminants. The 20- to 40-min protocol enabled a 4-log bioburden reduction down to <0.1 fmoles ATP detection limit (funnels and drill) to 0.2-0.7 fmoles (scoop) of total ATP. The (post-cleaning) hardware background was 0.3 to 1-2 attomoles ATP/cm2 (cleanliness benchmark background values) equivalent to ca. 1-10 colony forming unit (CFU)/cm2. Further, 60-100% of the in-sim hardware background was ≤3-4 bacterial cells/cm2, the threshold limit for Class <7 aseptic operations. Across the six Sols, the flux of airborne contaminants to the drill sites was ∼5 and ∼22 amoles ATP/(cm2·day), accounting for an unexpectedly high Fluorescence Intensity (FI) signal (FI: ∼6000) against aquatic cyanobacteria, but negligible anthropogenic contribution. The SOLID immunoassay also detected microorganisms from multiple habitats across the Atacama Desert (anoxic, alkaline/acidic microenvironments in halite fields, playas, and alluvial fans) in both airborne and post-cleaning hardware background. Finally, the hardware ATP background was 40-250 times lower than the ATP in cores. Similarly, the FI peaks (FImax) against the microbial taxa and molecular biomarkers detected in the post-cleaned hardware (FI: ∼1500-1600) were 5-10 times lower than biomarkers in drilled sediments, excluding significant interference with putative biomarker found in cores. Similar protocols enable the acquisition of contamination-free materials for ultra-sensitive instruments analysis and the integrity of scientific results. Their application can augment our scientific knowledge of the distribution of cryptic life on Mars-like grounds and support life-detection robotic and human-operated missions to Mars.

Design and development of latex cup collector robot

Global rubber production has declined over the past few years as a result of a number of variables, including both environmental and human factors. In this paper, an automated robot prototype that collects latex cups was developed to improve global rubber production by assisting workers in rubber plantations. The robot was built on a mobile platform with a motorized Five Degrees of Freedom (DoF) robotic arm, Ackermann steering, double wishbone suspension, rear-wheel drive and a latex storage tank to store the latex collected from the trees. The robot was equipped with ultrasonic sensors and a camera module to locate latex cups and rubber trees so that it could move and perform tasks accurately. In addition, encoder sensor modules were used to improve the accuracy of the movements by measuring the rotational speed of the motors. The yield strength of the PLA plastic material used in developing the latex cup collector robot is 7.00 x 107N/m2 and the maximum stress of the critical parts should not exceed the maximum yield strength of the PLA plastic. In mobility test, the robot is able to travel through obstacles of 10mm and 15mm height. The topple angle of the robot in the balancing test is greater than 37°, ensuring the stability of the robot.

Design of Power Tower Climbing Robot

The maintenance of high-voltage transmission lines mainly relies on manual work. When workers climb power towers, tower climbing robots are needed to provide safety ropes. In this paper, a power tower climbing robot with a new structure is designed, and its three-dimensional model is created and simulated. Finally, combined with the motor selection in each robot component, the tower climbing robot prototype was made and tested. The designed climbing robot can complete the locking and crawl on the power tower.

Dynamic and Real-Time Object Detection Based on Deep Learning for Home Service Robots

Home service robots operating indoors, such as inside houses and offices, require the real-time and accurate identification and location of target objects to perform service tasks efficiently. However, images captured by visual sensors while in motion states usually contain varying degrees of blurriness, presenting a significant challenge for object detection. In particular, daily life scenes contain small objects like fruits and tableware, which are often occluded, further complicating object recognition and positioning. A dynamic and real-time object detection algorithm is proposed for home service robots. This is composed of an image deblurring algorithm and an object detection algorithm. To improve the clarity of motion-blurred images, the DA-Multi-DCGAN algorithm is proposed. It comprises an embedded dynamic adjustment mechanism and a multimodal multiscale fusion structure based on robot motion and surrounding environmental information, enabling the deblurring processing of images that are captured under different motion states. Compared with DeblurGAN, DA-Multi-DCGAN had a 5.07 improvement in Peak Signal-to-Noise Ratio (PSNR) and a 0.022 improvement in Structural Similarity (SSIM). An AT-LI-YOLO method is proposed for small and occluded object detection. Based on depthwise separable convolution, this method highlights key areas and integrates salient features by embedding the attention module in the AT-Resblock to improve the sensitivity and detection precision of small objects and partially occluded objects. It also employs a lightweight network unit Lightblock to reduce the network’s parameters and computational complexity, which improves its computational efficiency. Compared with YOLOv3, the mean average precision (mAP) of AT-LI-YOLO increased by 3.19%, and the detection precision of small objects, such as apples and oranges and partially occluded objects, increased by 19.12% and 29.52%, respectively. Moreover, the model inference efficiency had a 7 ms reduction in processing time. Based on the typical home activities of older people and children, the dataset Grasp-17 was established for the training and testing of the proposed method. Using the TensorRT neural network inference engine of the developed service robot prototype, the proposed dynamic and real-time object detection algorithm required 29 ms, which meets the real-time requirement of smooth vision.

STUDY THE PERFORMANCE OF TWO-WHEELED BALANCING MOBILE ROBOT USING FUZZY PD CONTROLLER

Nowadays, the research on a two-wheeled self-balancing robot is an active area of research especially in terms of design as well as control to continue the innovation applications of robots in the future. Most of the two-wheeled self-balancing robots are designed based on an inverted pendulum system for stability and maneuverability. The aim of this paper is to propose the fuzzy PD controller to control and maintain its balance on the two wheels. A sensor of the Inertial Measurement Unit (IMU) was used as an input to evaluate and obtain the position and orientation of the robot. The control algorithms for the robot also are designed to keep the pendulum upright. Then, the fuzzy PD concept was applied to correct the error between the desired set point and the actual tilt angle position to adjust the speed of the motor accordingly. The results obtained from this controller were capable of maintaining the balancing of the robot by using an experimental method of PID tuning. The prototype of the two-wheeled self-balancing robot was implemented with Arduino Uno and a fuzzy PD controller. However, the limitation of the project is the longer size and heavier weight of the robot are less stable, then a better controller is needed to balance the robot.

Cable Robots as Conventional Linear Stage Alternatives for the Investigation of Complex-Shaped Objects via Macroscopic X-ray Fluorescence Imaging

The acquisition of elemental and chemical distribution images on the surface of cultural heritage objects has provided us new insights into our past. The techniques commonly employed, such as macroscopic X-ray fluorescence imaging (MA-XRF), in general require pointwise or whisk-broom scanning of an object under constant measurement geometry for optimal results. Most scanners in this field use stacked linear motorized stages, which are a proven solution for 2D sample positioning. Instead of these serial systems, we propose the use of a parallel cable robot to position the measurement head relative to the object investigated. In this article, we illustrate the significance of the issue and present our own cable robot prototype and test its capabilities, but also discuss the current shortcomings of the concept. With this, we demonstrate the potential of cable robots as platforms for MA-XRF and similar imaging techniques.

Fruit growing direction recognition and nesting grasping strategies for tomato harvesting robots

AbstractIn recent years, the potential of robotic harvesting in greenhouse tomato production has garnered significant attention within the tomato industry. However, there is a lack of sufficient research on the complete replacement of manual harvesting with this technology. In this paper, we propose a tomato harvesting method that utilizes a nesting approach to simplify the process and minimize damage. The paper describes the tomato harvesting robot prototype, the visual system equipped with three vision‐based tomato detectors: YOLOv5_CBAM, which incorporates a convolutional block attention module; YOLOv5_SE, enhanced with a squeeze‐and‐excitation block; and a standard YOLOv5s model. Additionally, a novel shear gripping method for fruit bunches is presented, utilizing a bottom‐up snapping technique during harvesting. Point cloud data are utilized to determine the position of the tomato's main stem and bunch. The paper includes field tests and experimental findings, which indicate that the YOLOv5_CBAM model achieves the highest precision (82.62%) and recall (82.57%), outperforming YOLOv5_SE and standard YOLOv5s. Field experiments demonstrate that the improved end‐effector and vision system have significantly enhanced the robot's performance, achieving a 57.5% harvesting success rate in just 14.9 s.

“It Brings the Good Vibes”: Exploring Biomorphic Aesthetics in the Design of Soft Personal Robots

The flexible bodies of soft robots provide exciting new possibilities for interaction with humans. In this paper, we propose a novel design paradigm, Soft Biomorphism, for soft robots centered on the idea of amplifying their inherent biomorphic aesthetic qualities and activating these as affordances for human interaction. Following this approach, we developed a set of biomorphic soft robotic prototypes and conducted two studies to understand the effects of biomorphic design aesthetics on people’s impressions of these prototypes. Based on qualitative data collected through five workshop sessions, the first exploratory study (n = 10) sought to investigate the envisioned uses and types of interactions that prototypes elicited within the context of personal robots. We found that various uses were considered and that most participants associated the biomorphic aesthetic design with soft robots contributing to emotional and physical well-being. Building on these results, we conducted a second study (n = 32) to investigate if soft robots with enhanced biomorphic qualities are perceived as more appealing and appropriate for physical human–robot interaction aimed at supporting well-being. We did not find any statistically significant preference for biomorphic soft robots. However, we found statistically significant differences in appeal ratings post-interaction for some prototypes, suggesting that physical interaction with soft robots can impact the perceived appeal. Based on our findings, we highlight key issues to bear in mind when considering biomorphic aesthetics in soft personal robot designs and provide tentative design recommendations to combine biomorphic and geometric elements and align visual appearance, tactility, and movement in future robot designs.