Collective Robotics Research Articles

The Development of a Tennis Ball Collection Robot Using Image Processing Algorithms

The Development of a Tennis Ball Collection Robot Using Image Processing Algorithms

Enhancing radioactive environment exploration with bio-inspired swarm robotics: A comparative analysis of Lévy flight and stigmergy methods

Utilizing swarm robotics techniques can significantly enhance the efficiency of exploring and mapping hazardous environments, such as nuclear sites. Instead of relying on a single robot for exploration, employing multiple robots working in coordination allows for fast coverage and more comprehensive data collection. In this study, bio-inspired algorithms, specifically Lévy flight and stigmergy, are utilized to guide the robots' movements. The Lévy flight algorithm mimics the movement patterns observed in animals like sharks and honeybees during their search for food, while stigmergy involves indirect communication between agents through environmental traces. By integrating these algorithms with swarm robotics, the robots effectively explore radioactive environments, gather data, and generate detailed maps of the area. Our research delves into various aspects of exploration, including the influence of the number of deployed robots and their exposure to radiation. Comparative analysis reveals the efficacy of stigmergy as a superior approach for guiding swarm robot movements in radioactive environments. This study underscores the significant potential of employing collective robotics for exploration tasks in nuclear scenarios, highlighting the promising applications of swarm intelligence in enhancing safety and efficiency in hazardous environments.

Body and Brain Quality-Diversity in Robot Swarms

In biological societies, complex interactions between the behavior and morphology of evolving organisms and their environment have given rise to a wide range of complex and diverse social structures. Similarly, in artificial counterparts such as swarm-robotics systems, collective behaviors emerge via the interconnected dynamics of robot morphology (sensory-motor configuration), behavior (controller), and environment (task). Various studies have demonstrated morphological and behavioral diversity enables biological groups to exhibit adaptive, robust, and resilient collective behavior across changing environments. However, in artificial (swarm robotic) systems there is little research on the impact of changing environments on morphological and behavioral (body-brain) diversity in emergent collective behavior, and the benefits of such diversity. This study uses evolutionary collective robotics as an experimental platform to investigate the impact of increasing task environment complexity (collective behavior task difficulty) on the evolution and benefits of morphological and behavioral diversity in robotic swarms. Results indicate that body-brain evolution using coupled behavior and morphology diversity maintenance yields higher behavioral and morphological diversity, which is beneficial for collective behavior task performance across task environments. Results also indicate that such behavioral and morphological diversity maintenance coupled with body-brain evolution produces neuro-morpho complexity that does not increase concomitantly with task complexity.

Autonomous Garbage Accumulation Robot using Internet of Things

All around the globe, the waste age rates are rising step by step. Overseeing litters appropriately is fundamental for building maintainable and decent conditions. Be that as it may, it has stayed Trash assortment has gotten hard to keep up or oversee by the individuals in their everyday life. Compelling trash the executives, less on city making plan. Regularly, unwanted things are arranged or are transparently scorched. Such practices have made add to worldwide atmosphere changes, serves a reproducing ground for ailment vectors, and furthermore elevates to urban viciousness. To beat these issues, we are building up an Autonomous Garbage Collecting Robot. This Robot is utilized to gather the trash from the containers. At the point when the containers are filled to a specific level, that receptacle sends a notice to the robot. Presently this robot is utilized to gather the trash from that specific receptacle and dumps the trash.

A trocar puncture robot for assisting venipuncture blood collection

AbstractThe venous blood test is a prevalent auxiliary medical diagnostic method. Venous blood collection equipment can improve blood collection’s success rate and stability, reduce the workload of medical staff, and improve the efficiency of diagnosis and treatment. This study proposed a rigid-flexible composite puncture (RFCP) strategy, based on which a small 7-degree-of-freedom (DOF) auxiliary venipuncture blood collection (VPBC) robot using a trocar needle was designed. The robot consists of a position and orientation adjustment mechanism and a RFCP end-effector, which can perform RFCP to avoid piercing the blood vessel’s lower wall during puncture. The inverse kinematics solution and validation of the robot were analyzed based on the differential evolution algorithm, after which the quintic polynomial interpolation algorithm was applied to achieve the robot trajectory planning control. Finally, the VPBC robot prototype was developed for experiments. The trajectory planning experiment verified the correctness of the inverse kinematics solution and trajectory planning, and the composite puncture blood collection experiment verified the feasibility of the RFCP strategy.

Multi-site Garbage Collection Robot based on Machine Vision

At present, the problem of garbage disposal has become an urgent problem to be solved in the global energy technology revolution and transformation and development. The mainstream garbage removal methods are manual picking and mechanical collection, which has low cleaning efficiency and high cleaning cost. In order to realize the convenient and efficient recycling and cleaning of land and water garbage, a new propeller dynamics model is proposed. Through the structural strength analysis and gas-liquid two-phase flow simulation analysis, combined with the aerodynamic theory, the propeller impeller model was optimized and its suitable working parameters were explored. Based on the paddle impeller mechanism, combined with the visual recognition and classification system controlled by the algorithm combining YOLO and template matching, a multi-site garbage recycling robot based on machine vision was designed, which realized the intelligent and multi-step integration of garbage recycling, and provided a new research idea for improving the way of garbage cleaning.

Path Planning of Agricultural Information Collection Robot Integrating Ant Colony Algorithm and Particle Swarm Algorithm

Path Planning of Agricultural Information Collection Robot Integrating Ant Colony Algorithm and Particle Swarm Algorithm

Research on Robot Operating System (ROS) Integration in Automated Logistics

Abstract In order to optimize the development of automated logistics, this paper proposes to build a mobile robot based on ROS to carry out intelligent autonomous navigation and distribution in the warehouse environment and to use intelligent robots to improve the efficiency of logistics and distribution. Analyze logistics robots’ localization methods and propose a SLAM algorithm to obtain environmental map information. Improve the Manhattan distance function to propose a global path planning A* algorithm based on the two-way search of the initial point and the target point, as well as a local path planning DWA algorithm to seek the best path. Collecting robot scheduling principles and scheduling conflict types, a genetic algorithm was selected for workshop AGV scheduling planning. Set up an experimental environment to analyze the optimal performance of the DWA algorithm. Combined with the intelligent warehouse goods sorting environment, analyze the planning and scheduling strategy for the goods sorting path of the ROS robot cluster. In the experiment, it is concluded that the larger the value of parameter β of the trajectory evaluation function is, the longer the time to be consumed by the calculation of the DWA algorithm is, and the designed path distance will be farther. When α =0.02 and β =0.2, the DWA algorithm reaches the best. Combined with the actual task scheduling path of the mobile robot cluster, it can be considered to be able to complete the autonomous navigation experiment in the whole warehouse environment, which is in line with the demand for automated logistics use.

Design of a Prairie Garbage Collection Robot Based on Unmanned Aerial Vehicles

In response to the increasing concern over environmental protection, particularly with regards to garbage pollution and degradation in prairie scenic areas, a solution is proposed involving a multi-rotor unmanned aerial vehicle (UAV) platform equipped with a mechanical arm for efficient prairie garbage collection. The potential applications of UAV technology incorporating a mechanical arm are discussed. The design of the mechanical apparatus is elaborated, encompassing components such as the UAV's mechanical arm, body frame, and telescopic pole. Consideration factors for the UAV frame are addressed to ensure design balance and stability. By integrating image transmission devices, visual recognition, and control systems, an automated process is achieved for identifying garbage locations, flying to the garbage position, grasping the waste, and successfully depositing it into the collection unit. Research findings demonstrate that the UAV equipped with a mechanical arm offers a proficient solution for garbage retrieval in prairie terrain, mitigating risks and costs associated with cleaning efforts.

Clinical application of a fully automated blood collection robot and its assessment of blood collection quality of anticoagulant specimens.

To investigate the application of intelligent puncture blood collection robots in anticoagulated blood specimens, the satisfaction of subjects with the two blood collection methods, and the feasibility of intelligent blood collection devices to replace manual blood collection methods in clinical work. A total of 154 volunteers from Zhongshan Hospital Fudan University were recruited to compare the test results of anticoagulant blood samples between blood collection robot and manual blood collection, a questionnaire was used to inquire about the volunteers' feelings about the two blood collection methods; the blood collection data of 6,255 patients willing to use the robot for blood collection were collected to analyze the success rate of blood collection. The blood collection robot is superior to manual specimen collection in terms of volume and pain of specimen collection, and the puncture success rate is 94.3%. The anticoagulated blood specimens collected by the robot had 11 indexes statistically different from the results of manual blood collection, but the differences did not affect the clinical diagnosis and prognosis. The intelligent robotic blood collection is less painful and has better acceptance by patients, which can be used for clinical anticoagulated blood specimen collection.

Development of an Internet of Things-Based Garbage Collection Robot

The problem of garbage is not a new thing from the past until now, garbage is still the center of attention and a prolonged problem because of the various impacts of the problems that are caused and felt. Many factors are the cause of the increasing amount of garbage every day, including the lack of self-awareness about maintaining cleanliness and disposing of garbage in its place. This study aims to develop an IoT-based garbage collection robot. The method in developing this garbage collection robot is using the Fuzzy Mamdani method. The IoT-based garbage collection robot is designed using the Arduino Uno microcontroller as well as the Node MCU ESP 8266, HC-SR04 sensor, DHT11 sensor, SG90 Servo motor, DC motor and L298N motor driver. The way this robot works is to detect the distance with the HC-SR04 sensor as a distance data input then processed by the Arduino microcontroller and then the SG90 servo motor will move to clamp the garbage automatically and for the robot using control via a smartphone to be directed to the destination garbage. The results of this study are that the robot can clamp or pick up garbage with a distance of less than 5 cm and can control the speed of a DC motor using the fuzzy Mamdani method.

Solar Based River Water Garbage Collector

This paper presents Arduino based project of a Solar powered Robot for Water Garbage collection is a self-sustaining, eco-friendly solution for cleaning up water bodies. The robot uses solar power to charge its batteries and is equipped with a garbage collection mechanism to collect and dispose of floating debris. The robot's navigation is controlled by an Arduino microcontroller, which uses sensors to detect obstacles and adjust its course accordingly. The robot's design is modular and can be adapted to different water body sizes and shapes. The robot has potential applications in a variety of industries, including municipal waste management, aquaculture, and environmental monitoring. This project demonstrates the potential of combining renewable energy and robotics to develop sustainable solutions for environmental challenges

EZMap: Boosting Automatic Floor Plan Construction With High-Precision Robotic Tracking

Indoor-location-based services rely on indoor maps, which are yet widely available despite numerous efforts from the industry. Existing solutions employ costly hardware (e.g., lidar) to achieve accurate mapping of indoor environments, or resort to crowdsourcing for floor plan generation at the cost of precision due to inaccurate inertial sensing. In this article, we leverage a new opportunity enabled by recent advances in RF-based inertial tracking that achieves centimeter accuracy. We present EZMAP, a high-accuracy, low-cost floor plan construction system that fuses RF and inertial sensing. EZMAP combines the fine-grained yet local information from RF tracking with the coarse grained but global contexts from inertial sensing (e.g., magnetic field strength), which together makes for an accurate map. Our system employs a robot for trajectory collection and requires only a single access point to be arbitrarily installed in the space, both of which are widely available nowadays. Furthermore, it can generate a map even only a small amount of data is available, allowing it to scale for different buildings, such as malls, office buildings, and homes with little cost. We validate the performance using a Dji RoboMaster S1 robot with commodity WiFi in three different buildings. The results show that our system can efficiently generate faithful maps for the targeted areas. With the ubiquity of the WiFi infrastructure and the rise of home robots, we believe our approach will pave the way for pervasive indoor maps services.

Conceptual design and simulation study of an autonomous indoor medical waste collection robot

Solid waste management is one of the critical challenges seen everywhere, and the coronavirus disease (COVID-19) pandemic has only worsened the problems in the safe disposal of infectious waste. This paper outlines a design for a mobile robot that will intelligently identify, grasp, and collect a group of medical waste items using a six-degree of freedom (DoF) arm, You Only Look Once (YOLO) neural network, and a grasping algorithm. Various designs are generated before running simulations on the selected virtual model using Robot Operating System (ROS) and Gazebo simulator. A lidar sensor is also used to map the robot's surroundings and navigate autonomously. The robot has good scope for waste collection in medical facilities, where it can help create a safer environment.

Development of a Vision-Based Unmanned Ground Vehicle for Mapping and Tennis Ball Collection: A Fuzzy Logic Approach

The application of robotic systems is widespread in all fields of life and sport. Tennis ball collection robots have recently become popular because of their potential for saving time and energy and increasing the efficiency of training sessions. In this study, an unmanned and autonomous tennis ball collection robot was designed and produced that used LiDAR for 2D mapping of the environment and a single camera for detecting tennis balls. A novel method was used for the path planning and navigation of the robot. A fuzzy controller was designed for controlling the robot during the collection operation. The developed robot was tested, and it successfully detected 91% of the tennis balls and collected 83% of them.

A Prototype of Garbage Picker Ship Robot Using Arduino Nano Microcontroller

This study aims to create a robot prototype for a garbage collection ship made using an Arduino nano microcontroller. The prototype of this garbage collection robot vessel is controlled by an Android smartphone application that is connected via Bluetooth. The prototype of the robot of the boat was made to deal with piles of garbage that can cause flooding. The method used in making the prototype ship robot along with the controller application begins with identifying the problem, namely the problem of piles of garbage, then needs analysis. Moreover, in this research, what will be developed is in terms of design, ship robot prototype, and ship robot controller design. Next is implementation and testing. The prototype of the garbage collection ship robot uses an Arduino nano microcontroller and in making a controller application using Android Basic 4. Then the trial stage was carried out on an Android smartphone. The results of this study are a prototype ship robot that can move according to commands through a controller application.

Configurable Waste Collecting Robot Using Deep Learning and Iot

Configurable Waste Collecting Robot Using Deep Learning and Iot

Embedded elbow vein blood collection robot system based on artificial intelligence technology

Embedded elbow vein blood collection robot system based on artificial intelligence technology

Embedded elbow vein blood collection robot system based on artificial intelligence technology

Embedded elbow vein blood collection robot system based on artificial intelligence technology

Path planning for data collection robot in sensing field with obstacles

Using mobile robots to collect data from wireless sensor network can reduce energy dissipation and this way improves network lifetime. Our problem is to plan paths for unicycle robots to visit a set of sensor nodes and download data on a sensing field with obstacles while minimizing the path length and the collecting time. Reconstructing the path of an intruder in a guarded area is also a possible application of this technology. During path planning we greatly emphasize the handling of obstacles. If the area contains many or large obstacles, the robots may spend long time for avoid them so this is a critical point of finding the minimal path. This paper proposes a new approach for handling obstacles during path planning. A new algorithm is developed to plan the visiting sequence of nodes taking into consideration the obstacles as well.