Exploring Elephant Robotics LIMO Cobot

1. Introduction:

This article primarily introduces the practical application of LIMO Cobot by Elephant Robotics in a simulated scenario. You may have seen previous posts about LIMO Cobot’s technical cases, A[LINK]B[LINK]. The reason for writing another related article is that the original testing environment, while demonstrating basic functionality, often appears overly idealized and simplified when simulating real-world applications. Therefore, we aim to use it in a more operationally consistent environment and share some of the issues that arose at that time.

2. Comparing the Old and New Scenarios:

First, let’s look at what the old and new scenarios are like.

Old Scenario: A simple setup with a few obstacles, relatively regular objects, and a field enclosed by barriers, approximately 1.5m*2m in size.

New Scenario: The new scenario contains a wider variety of obstacles of different shapes, including a hollowed-out object in the middle, simulating a real environment with road guidance markers, parking spaces, and more. The size of the field is 3m*3m.

The change in environment is significant for testing and demonstrating the comprehensiveness and applicability of our product.

3. Analysis of Practical Cases:

Next, let’s briefly introduce the overall process.

The process is mainly divided into three modules: one is the functionality of LIMO PRO, the second is machine vision processing, and the third is the functionality of the robotic arm. (For a more detailed introduction, please see the previous article [link].)

LIMO PRO is mainly responsible for SLAM mapping, using the gmapping algorithm to map the terrain, navigate, and ultimately achieve the function of fixed-point patrol.

myCobot 280 M5 is primarily responsible for the task of grasping objects. A camera and a suction pump actuator are installed at the end of the robotic arm. The camera captures the real scene, and the image is processed by the OpenCV algorithm to find the coordinates of the target object and perform the grasping operation.

Overall process:

1. LIMO performs mapping.⇛

2. Run the fixed-point cruising program.⇛

3. LIMO goes to point A ⇛ myCobot 280 performs the grasping operation ⇒ goes to point B ⇛ myCobot 280 performs the placing operation.

4. ↺ Repeat step 3 until there are no target objects, then terminate the program.

Next, let’s follow the practical execution process.


First, you need to start the radar by opening a new terminal and entering the following command:

roslaunch limo_bringup limo_start.launch pub_odom_tf:=false

Then, start the gmapping mapping algorithm by opening another new terminal and entering the command:

roslaunch limo_bringup limo_gmapping.launch

After successful startup, the rviz visualization tool will open, and you will see the interface as shown in the figure.

At this point, you can switch the controller to remote control mode to control the LIMO for mapping.

After constructing the map, you need to run the following commands to save the map to a specified directory:

1. Switch to the directory where you want to save the map. Here, save the map to `~/agilex_ws/src/limo_ros/limo_bringup/maps/`. Enter the command in the terminal:

cd ~/agilex_ws/src/limo_ros/limo_bringup/maps/

2. After switching to `/agilex_ws/limo_bringup/maps`, continue to enter the command in the terminal:

rosrun map_server map_saver -f map1

This process went very smoothly. Let’s continue by testing the navigation function from point A to point B.


1. First, start the radar by entering the following command in the terminal:

roslaunch limo_bringup limo_start.launch pub_odom_tf:=false

2. Start the navigation function by entering the following command in the terminal:

roslaunch limo_bringup limo_navigation_diff.launch

Upon success, this interface will open, displaying the map we just created.

Click on „2D Pose Estimate, “ then click on the location where LIMO is on the map. After starting navigation, you will find that the shape scanned by the laser does not overlap with the map. You need to manually correct this by adjusting the actual position of the chassis in the scene on the map displayed in rviz. Use the tools in rviz to publish an approximate position for LIMO. Then, use the controller to rotate LIMO, allowing it to auto-correct. When the shape of the laser scan overlaps with the shapes in the map’s scene, the correction is complete, as shown in the figure where the scanned shape and the map overlap.

Click on „2D Nav Goal“ and select the destination on the map for navigation.

The navigation test also proceeds smoothly.

Next, we will move on to the part about the static robotic arm’s grasping function.

Identifying and Acquiring the Pose of Aruco Codes

To precisely identify objects and obtain the position of the target object, we processed Aruco codes. Before starting, ensure the specific parameters of the camera are set.

Initialize the camera parameters based on the camera being used.

def __init__(self, mtx: np.ndarray, dist: np.ndarray, marker_size: int):
self.mtx = mtx
self.dist = dist
self.marker_size = marker_size
self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
self.parameters = cv2.aruco.DetectorParameters_create()

Then, identify the object and estimate its pose to obtain the 3D position of the object and output the position information.

def estimatePoseSingleMarkers(self, corners):
This will estimate the rvec and tvec for each of the marker corners detected by:
corners, ids, rejectedImgPoints = detector.detectMarkers(image)
corners - is an array of detected corners for each detected marker in the image
marker_size - is the size of the detected markers
mtx - is the camera matrix
distortion - is the camera distortion matrix
RETURN list of rvecs, tvecs, and trash (so that it corresponds to the old estimatePoseSingleMarkers())
marker_points = np.array([[-self.marker_size / 2, self.marker_size / 2, 0],
[self.marker_size / 2, self.marker_size / 2, 0],
[self.marker_size / 2, -self.marker_size / 2, 0],
[-self.marker_size / 2, -self.marker_size / 2, 0]], dtype=np.float32)
rvecs = []
tvecs = []
for corner in corners:
retval, rvec, tvec = cv2.solvePnP(marker_points, corner, self.mtx, self.dist, False,
if retval:

rvecs = np.array(rvecs)
tvecs = np.array(tvecs)
(rvecs - tvecs).any()
return rvecs, tvecs

The steps above complete the identification and acquisition of the object’s information, and finally, the object’s coordinates are returned to the robotic arm to execute the grasping.

Robotic Arm Movement and Grasping Operation

Based on the position of the Aruco marker, calculate the target coordinates the robotic arm needs to move to and convert the position into a coordinate system suitable for the robotic arm.

def homo_transform_matrix(x, y, z, rx, ry, rz, order="ZYX"):
rot_mat = rotation_matrix(rx, ry, rz, order=order)
trans_vec = np.array([[x, y, z, 1]]).T
mat = np.vstack([rot_mat, np.zeros((1, 3))])
mat = np.hstack([mat, trans_vec])
return mat

If the Z-axis position is detected as too high, it will be corrected:

if end_effector_z_height is not None:  
p_base[2] = end_effector_z_height

After the coordinate correction is completed, the robotic arm will move to the target position.

# Concatenate x, y, z, and the current posture into a new array
new_coords = np.concatenate([p_base, curr_rotation[3:]])
xy_coords = new_coords.copy()

Then, control the end effector’s API to suction the object.

The above completes the respective functions of the two robots. Next, they will be integrated into the ROS environment.

#Initialize the coordinates of point A and B
    goal_1 = [(2.060220241546631,-2.2297520637512207,0.009794792000444471,0.9999520298742676)] #B
    goal_2 = [(1.1215190887451172,-0.002757132053375244,-0.7129997613218174,0.7011642748707548)] #A
    #Start navigation and link the robotic arm
    map_navigation = MapNavigation()
    arm = VisualGrasping("",9000)
    print("connect successful")

    # Navigate to location A and perform the task
        for goal in goal_1:
        x_goal, y_goal, orientation_z, orientation_w = goal
        flag_feed_goalReached = map_navigation.moveToGoal(x_goal, y_goal, orientation_z, orientation_w)
        if flag_feed_goalReached:
            # executing 1 grab and setting the end effector's Z-axis height to -93.
            print("command completed")

4. Problems Encountered

Mapping Situation:

When we initially tried mapping without enclosing the field, frequent errors occurred during navigation and localization, and it failed to meet our requirements for a simulated scenario.

Navigation Situation:

In the new scenario, one of the obstacles has a hollow structure.

During navigation from point A to point B, LIMO may fail to detect this obstacle and assume it can pass through, damaging the original obstacle. This issue arises because LIMO’s radar is positioned low, scanning only the empty space. Possible solutions include adjusting the radar’s scanning range, which requires extensive testing for fine-tuning, or adjusting the radar’s height to ensure the obstacle is recognized as impassable.

Robotic Arm Grasping Situation:

In the video, it’s evident that our target object is placed on a flat surface. The grasping did not consider obstacle avoidance for the object. In the future, when setting special positions for grasping, this situation needs to be considered.

5. Conclusion

Overall, LIMO Cobot performed excellently in this scenario, successfully meeting the requirements. The entire simulated scenario covered multiple core areas of robotics, including motion control of the robotic arm, path planning, machine vision recognition and grasping, and radar mapping navigation and fixed-point cruising functions of the mobile chassis. By integrating these functional modules in ROS, we built an efficient automated process, showcasing LIMO Cobot’s broad adaptability and advanced capabilities in complex environments.


Elephant Robotics

Elephant Robotics

Elephant Robotics stellt myArm-Roboter der M&C-Serie vor

Entdecken Sie die Roboter der myArm M&C-Serie für vielseitige, leistungsstarke Lösungen in der Robotik, die eine präzise Steuerung und vielfältige Anwendungen bieten.

SHENZHEN, GUANGDONG, CHINA, 10. Mai 2024 /EINPresswire.com/ — Die Forschung zur verkörperten Intelligenz als kritischer Zweig der künstlichen Intelligenz ist bestrebt, Roboter mit neuen Fähigkeiten für präzise Bewegungssteuerung, autonome Entscheidungsfindung auf hohem Niveau und nahtlose Mensch-Maschine-Interaktion auszustatten.

Vor diesem Hintergrund hat Elephant Robotics kürzlich die Roboter der M&C-Serie myArm vorgestellt. Diese leistungsstarken und kostengünstigen Leichtbauroboter unterstützen Forscher und Entwickler sowohl bei der Datenerfassung als auch bei der Ausführung und treiben die Fortschritte in der Technologie der verkörperten Intelligenz und ihrer praktischen Anwendungen voran.

Die Roboter der myArm M&C-Serie wurden sorgfältig entwickelt, um die unterschiedlichen Bedürfnisse der Benutzer zu erfüllen, wobei Flexibilität und Anpassungsfähigkeit im Vordergrund stehen. Sie spielen eine zentrale Rolle in verschiedenen Forschungs- und Anwendungsszenarien und sind damit die ideale Robotiklösung für Bildungs- und Forschungszwecke.

myArm C650

The myArm C650 ist ein universelles 6-DOF-Gerät zur Erfassung von Roboterbewegungsinformationen, das entwickelt wurde, um die vielfältigen Anforderungen von Bildung, Forschung und Industrie bei der Erfassung und Analyse von Roboterbewegungsdaten zu erfüllen. Mit seinem leichten Design von nur 1,8 kg verfügt der myArm C650 über einen horizontalen Arbeitsradius von 650 mm, wodurch die Trägheitskräfte während des Betriebs minimiert werden, um die Reaktionsgeschwindigkeit und Präzision zu verbessern.

Ausgestattet mit hochpräzisen digitalen Servomotoren und 4096-Bit-Encodern an allen 6 Gelenken ahmt der myArm C650 die Bewegung des menschlichen Arms mit bemerkenswerter Genauigkeit nach und ermöglicht so eine Vielzahl von Aufgaben. Seine intuitive Steuerungsmethode mit Doppelfinger-Fernbedienung und zwei anpassbaren Tasten unterstützt Aufzeichnungsfunktionen für eine präzise Befehlsausführung und sofortiges Feedback zum Roboterverhalten. Diese Flexibilität macht den myArm C650 zur idealen Wahl für die präzise Bewegungsverfolgung und Datenerfassung in verschiedenen experimentellen und pädagogischen Umgebungen. Mit einer beeindruckenden Informationserfassungsgeschwindigkeit von bis zu 50 Hz ist es für die Entwicklung von Roboteralgorithmen und Hochschuleinrichtungen unverzichtbar geworden und bietet Echtzeit-Datenunterstützung für komplexe Steuerungssysteme.

Bei Fernsteuerungsanwendungen zeichnet sich der myArm C650 durch eine hervorragende Leistung aus, unabhängig von der Komplexität der Konfiguration des Roboters. Darüber hinaus erweitert die Kompatibilität mit Python und ROS in Verbindung mit Open-Source-Demonstrationsdateien für die Fernsteuerung den Anwendungsbereich und ermöglicht eine nahtlose Integration mit fortschrittlichen Roboterplattformen wie dem myArm M750, myCobot Pro 630 und Mercury B1.

Der myArm C650 setzt einen neuen Standard für Vielseitigkeit und Leistung bei der Erfassung von Roboterbewegungsdaten und ermöglicht es Benutzern, das volle Potenzial fortschrittlicher Robotik in verschiedenen Bereichen auszuschöpfen.

myArm M750

Der myArm M750 ist ein universeller, intelligenter 6-DOF-Roboterarm. Es erfüllt nicht nur die Nachfrage nach hochpräziser Roboterbewegungssteuerung, sondern eignet sich besonders für die Verifizierung von Roboterbewegungsalgorithmen auf Einstiegsniveau und praktische Lehrszenarien. Seine standardisierte mechanische Armstruktur bietet Studenten und Anfängern eine ideale Lernplattform, um die Grundprinzipien und Anwendungen der Roboterkinematik zu verstehen.

Der myArm M750 wurde für eine präzise Bewegungssteuerung und -verifizierung entwickelt und eignet sich hervorragend für Anwendungen, die eine strenge Betriebsgenauigkeit erfordern, wie z. B. Präzisionsmontage, Feinmanipulation und Qualitätsüberwachung. Ausgestattet mit hochpräzisen digitalen Servomotoren in Industriequalität und fortschrittlichen Steuerungsalgorithmen bietet der myArm M750 eine außergewöhnliche Drehmomentsteuerung und Positionsgenauigkeit und unterstützt eine Nenntragfähigkeit von 500 g und eine Spitzenlast von bis zu 1 kg.

Die Vielseitigkeit des myArm M750 erstreckt sich auch auf das Endeffektor-Design, das mit einem standardmäßigen Parallelgreifer und einem Vision-Modul ausgestattet ist, das dem Benutzer grundlegende Greif- und Erkennungsfunktionen bietet. Darüber hinaus bietet der myArm M750 Kompatibilität mit einer Reihe von optionalem Zubehör, was seine Anwendungsszenarien und Anpassungsfähigkeit an verschiedene Aufgaben erheblich erweitert.

myArm M&C Teleoperation Roboterarm-Kit

DasTeleoperation Robotic Arm Kit stellt einen Sprung nach vorne in der Robotik-Innovation dar und bietet eine fortschrittliche Lösung, die auf die Fernsteuerung und Echtzeit-Interaktion durch modernste Teleoperationstechnologie zugeschnitten ist. Durch die nahtlose Integration der Vielseitigkeit des myArm C650 mit den präzisen Steuerungsfunktionen des myArm M750 bildet dieses Kit eine dynamische und anpassungsfähige Plattform, die für eine Vielzahl von Forschungs-, Bildungs- und kommerziellen Anwendungen geeignet ist.

Das Kit wurde entwickelt, um menschliches Verhalten nachzuahmen, und ermöglicht es Forschern und Entwicklern, Fernsteuerungssysteme und Roboterbewegungsplanungsmodelle ähnlich dem ALOHA-Roboter zu validieren und zu testen. Das myArm M&C Kit verfügt über Datenerfassungs- und Steuerungsfunktionen auf Millisekundenebene, Echtzeit-Widerstandssteuerungsfunktionen und kollaborative Betriebsfunktionen mit mehreren Robotern und erleichtert die Ausführung komplexer Aufgaben, einschließlich fortschrittlicher Simulationen menschlichen Verhaltens. Diese Technologie zeigt nicht nur die Präzision und Effizienz von Robotern bei der Nachahmung menschlicher Handlungen, sondern treibt auch die Forschung und Entwicklung in der Robotertechnologie zur Simulation menschlichen Verhaltens und zur Ausführung alltäglicher Aufgaben voran.

Darüber hinaus stattet die integrierte KI-Technologie Roboter mit Lern- und Anpassungsfähigkeit aus, ermöglicht autonome Navigation, Objekterkennung und komplexe Entscheidungsfähigkeiten und erschließt so ein enormes Anwendungspotenzial in verschiedenen Forschungsbereichen.

myArm M&C Embodied humanoid Robot Compound Kit

Das Mobile ALOHA-Projekt der Stanford University hat aufgrund seiner bahnbrechenden Fortschritte in der Robotiktechnologie weltweite Aufmerksamkeit erregt. Es hat ein fortschrittliches System entwickelt, das es Benutzern ermöglicht, komplexe zweiarmige Aufgaben durch menschliche Demonstrationen auszuführen und so die Effizienz von nachgeahmten Lernalgorithmen durch Datenakkumulation und kollaboratives Training zu verbessern. Das Mobile ALOHA-System zeigt seine Vielseitigkeit, indem es verschiedene reale Aufgaben nahtlos ausführt, vom Reinigen verschütteter Getränke über das Kochen von Garnelen bis hin zum Waschen von Bratpfannen. Diese Innovation markiert nicht nur einen bedeutenden Meilenstein in der Robotik, sondern ebnet auch den Weg für eine Zukunft, in der Mensch und Roboter harmonisch koexistieren.

Dieses Kit wurde von Stanfords Mobile ALOHA-Projekt inspiriert und verwendet das gleiche mobile Tracer-Fahrgestell. Mit einer Open-Source-Philosophie, minimalistischem Design, modularem Aufbau und robuster lokaler Community-Unterstützung dient dieses Kit als kostengünstige Lösung für die Echtzeit-Roboterteleoperation und -steuerung und spiegelt die Fähigkeiten von Mobile ALOHA zu einem erschwinglicheren Preis wider.

Dieses Kit wurde entwickelt, um den Bedürfnissen kleiner und mittlerer Unternehmen sowie Bildungs- und Forschungseinrichtungen gerecht zu werden, und bietet einen erschwinglicheren Preis, benutzerfreundliche Funktionen und einen einfachen Zugang zu modernster Robotertechnologie.

Die Roboter der myArm M&C-Serie sind eine vielseitige Robotiklösung, die unterschiedliche Anforderungen erfüllt, von der Grundlagenforschung bis hin zur Ausführung komplizierter Aufgaben. In Kombination mit optionalen Kits passen sie sich nahtlos an verschiedene Anwendungsszenarien an, von der Präzisionsfertigung über medizinische Hilfe bis hin zu Bildung, Schulung und Haushaltsunterstützung. Die Roboter der myArm M&C-Serie zeichnen sich durch zuverlässige und leistungsstarke Lösungen aus, die Zuverlässigkeit und Exzellenz versprechen. Die Aufnahme des Embodied Humanoid Robot Compound Kit und des Quadruped Bionic Robot Compound Kit erweitert die Möglichkeiten in der Robotik weiter, fördert die interdisziplinäre Erforschung und fördert Innovationen.

Elephant Robotics Unveils myArm M&C Series Robots to Advance Embodied Intelligence

Explore myArm M&C series robots for versatile, high-performing solutions in robotics, offering precise control and diverse applications.

SHENZHEN, GUANGDONG, CHINA, May 10, 2024 /EINPresswire.com/ — Embodied intelligence research, as a critical branch of artificial intelligence, is striving to endow robots with new capabilities in precise motion control, high-level autonomous decision-making, and seamless human-machine interaction.

Against this backdrop, Elephant Robotics has recently unveiled the myArm M&C series robots. These powerful and cost-effective lightweight robots empower researchers and developers in both data collection and execution, driving forward the advancements in embodied intelligence technology and its practical applications..

The myArm M&C series robots are meticulously designed to meet the diverse needs of users, prioritizing flexibility and adaptability. They play a pivotal role in various research and application scenarios, making them the ideal robotics solution for education and research purposes.

myArm C650

The myArm C650 is a universal 6 DOF robot motion information collection device designed to meet the diverse needs of education, research, and industry in robot motion data collection and analysis. With its lightweight design of weighing only 1.8kg, the myArm C650 boasts a horizontal working radius of 650mm, minimizing inertial forces during operation for enhanced response speed and precision.

Equipped with high-precision digital servo motors and 4096-bit encoders on all 6 joints, the myArm C650 mimics human arm motion with remarkable accuracy, enabling a wide range of tasks. Its intuitive control method, featuring dual-finger remote control and dual customizable buttons, supports recording functions for precise command execution and immediate feedback on robot behavior. This flexibility makes the myArm C650 an ideal choice for precise motion tracking and data collection in various experimental and educational settings. With an impressive information acquisition speed of up to 50Hz, it has become indispensable for robot algorithm development and higher education institutions, offering real-time data support for complex control systems.

In remote control applications, the myArm C650 excels, delivering outstanding performance regardless of the robot’s configuration complexity. Moreover, its compatibility with Python and ROS, coupled with open-source remote control demonstration files, expands its application scope, enabling seamless integration with advanced robot platforms like the myArm M750, myCobot Pro 630, and Mercury B1.

The myArm C650 sets a new standard for versatility and performance in robot motion data collection, empowering users to explore the full potential of advanced robotics across diverse fields.

myArm M750

The myArm M750 is a universal intelligent 6 DOF robotic arm. It not only meets the demand for high-precision robot motion control but is particularly suitable for entry-level robot motion algorithm verification and practical teaching scenarios. Its standardized mechanical arm structure provides an ideal learning platform for students and beginners to grasp the basic principles and applications of robot kinematics.

Dedicated to achieving precise motion control and verification, the myArm M750 excels in applications requiring strict operational accuracy, such as precision assembly, fine manipulation, and quality monitoring. Equipped with industrial-grade high-precision digital servo motors and advanced control algorithms, the myArm M750 delivers exceptional torque control and positional accuracy, supporting a rated load capacity of 500g and a peak load of up to 1kg.

The myArm M750’s versatility extends to its end effector design, featuring a standard parallel gripper and vision module that empower users with basic grasping and recognition capabilities. Furthermore, the myArm M750 offers compatibility with a range of optional accessories, significantly expanding its application scenarios and adaptability to diverse tasks.

myArm M&C Teleoperation Robotic Arm Kit

Teleoperation Robotic Arm Kit represents a leap forward in robotics innovation, offering an advanced solution tailored for remote control and real-time interaction through cutting-edge teleoperation technology. By seamlessly integrating the versatility of the myArm C650 with the precise control capabilities of the myArm M750, this kit forms a dynamic and adaptable platform suitable for a myriad of research, educational, and commercial applications.

Engineered to mimic human behavior, the kit enables researchers and developers to validate and test remote control systems and robot motion planning models akin to the ALOHA robot. Empowered by millisecond-level data acquisition and control capability, real-time drag control functionality, and multi-robot collaborative operation capabilities, the myArm M&C Kit facilitates the execution of complex tasks, including advanced simulations of human behavior. This technology not only showcases the precision and efficiency of robots in mimicking human actions but also propels research and development in robot technology for simulating human behavior and performing everyday tasks.

Moreover, integrated AI technology equips robots with learning and adaptability, enabling autonomous navigation, object recognition, and complex decision-making capabilities, thereby unlocking vast application potential across diverse research fields.

myArm M&C Embodied Humanoid Robot Compound Kit

Stanford University’s Mobile ALOHA project has garnered global attention for its groundbreaking advancements in robotics technology. It has developed an advanced system that allows users to execute complex dual-arm tasks through human demonstrations, thereby enhancing imitation learning algorithms‘ efficiency through data accumulation and collaborative training. The Mobile ALOHA system showcases its versatility by seamlessly executing various real-world tasks, from cleaning spilled drinks to cooking shrimp and washing frying pans. This innovation not only marks a significant milestone in robotics but also paves the way for a future where humans and robots coexist harmoniously.

Drawing inspiration from Stanford’s Mobile ALOHA project, this kit adopts the same Tracer mobile chassis. With an open-source philosophy, minimalist design, modular construction, and robust local community support, this kit serves as a cost-effective solution for real-time robot teleoperation and control, mirroring the capabilities of Mobile ALOHA with a more accessible price.

Designed to cater to the needs of small and medium-sized enterprises, as well as educational and research institutions, this kit offers a more accessible price, user-friendly features, and easy accessibility to cutting-edge robot technology.

The myArm M&C series robots are a versatile robotics solution catering to diverse needs from fundamental research to intricate task execution. In combination with optional kits, they seamlessly adapt to various application scenarios, from precision manufacturing to medical assistance, education, training, and household support. The myArm M&C series robots stand out as dependable and high-performing solutions, promising reliability and excellence. The inclusion of the Embodied Humanoid Robot Compound Kit and Quadruped Bionic Robot Compound Kit further expands the possibilities in robotics, encouraging interdisciplinary exploration and fostering innovation.

Qviro Helps Robotics Buyers Make Transparent Choices with Biggest Marketplace

Qviro Revolutionizes Robotics Buying Experience

Qviro, one of the leading robotics platforms, introduces a groundbreaking marketplace, offering unparalleled transparency and choice. Users can effortlessly compare the full robotics market and access a vast selection of 211 cobots

The platform ensures transparent pricing, allowing buyers access to all cobot prices on Qviro. For added assistance, it provides an average cobot price of €27,158. Additionally, Qviro includes 400+ user reviews for informed decisions.

In the cobot category, Universal Robots leads with a 4.6 rating from over 41 user reviews. Their products excel in ease of use and integration, favored by engineers and enthusiasts.

For budget-conscious buyers, Elephant Robotics and Wlkata offer educational robots starting at $599. They provide cost-effective solutions for educational and hobbyist projects. Find Elephant Robotics‘ products at Elephant Robotics Products and Wlkata’s at Wlkata Products.

Sven De Donder, Co-CEO of Qviro, said, „Our user base in Europe and North America is growing exponentially due to unmatched transparency.“

Qviro transforms the robotics buying experience, offering an all-in-one solution for enthusiasts and professionals. With diverse options, transparent pricing, and a supportive user community, Qviro meets all your robotics needs.

About Qviro:

Qviro is a Belgium-based startup that is revolutionising the procurement process of industrial technology such as robots and machines through digitization. The company’s review platform, Qviro.com, provides factories and engineers with valuable insights and customer feedback to make confident purchasing decisions. At the same time, it offers vendors market intelligence and data to help them better understand their potential customers. As a SaaS platform, Qviro is dedicated to providing exceptional customer experiences and innovative solutions that drive growth and progress in the industry. To learn more about Qviro, visit www.Qviro.com.

Elephant Robotics launched ultraArm with various solutions for education

In the past year, Elephant Robotics has launched various products to meet more user needs and help them unlock more potential in research and education. To help users learn more knowledge about machine vision, Elephant Robotics launched the AI Kit, which can work with multiple robotic arms to do AI recognition and grabbing. In June 2022, Elephant Robotics released the mechArm to help individual makers and students get better learning in industrial robotics.

Nowadays, robotic arms are used in an increasingly wide range of applications, such as industry, medicine, commercial exhibitions, etc. At the very end of 2022, ultraArm is launched, and this time, Elephant Robotics doesn’t just release a new robotic arm, but brings 5 sets of solutions to education and R&D.

Small but powerful

As the core product of this launch, ultraArm is a small 4-axis desktop robotic arm. It is designed with a classic metal structure and occupies only an area of A5 paper. It is the first robotic arm equipped with a high-performance stepper motors of Elephant Robotics. It is stable and owns ±0.1mm repeated positioning accuracy. What’s more, ultraArm comes with 5 kits together including slide rail, conveyor belt, and cameras.

Multiple environments supported

As a preferred tool for the education field, ultraArm supports all major programming languages, including Python, Arduino, C++, etc. Also, it can be programmed in Mac, Windows, and Linux systems. For individual makers who are new to robotics, they can learn robotic programming with myBlockly, a visualization software that allows users to drag and drop code blocks.

Moreover, ultraArm supports ROS1 & ROS2. In the ROS environment, users can control ultraArm and verify algorithms in the virtual environment, improving experiment efficiency. With the support of ROS2, users can achieve more functions and objects in the developments.

Five robotic kits with for Robot Vision & DIY

In the past year, Elephant Robotics found that many users have to spend large amount of time creating accessories or kits to work with robotic arms. Therefore, to provide more solutions in different fields, ultraArm comes with five robotic kits, which are devided into two series: vision educational kits and DIY kits. These kits will help users, especially students program easily for a better learning experience on practical exercises about AI robot vision and DIY robotic projects.

Vision educational kits

Combined with vision functions, robotic arms can be used for more applications in industry, medicine, education, etc. In robotics education, collaborative robotic arms with vision capabilities allow students to better learn about artificial intelligence. Elephant Robotics has launched three kits for machine vision education: Vision & Picking Kit, Vision & Conveyor Belt Kit, and Vision & Slide Rail Kit to provide more choices and support to the education industry. With the camera and built-in related AI algorithms (Yolo, SIFT, ORB, etc.), ultraArm can achieve different artificial intelligence recognition applications with different identifying ways. Therefore, users can select the kit based on their needs.

For Vision & Picking Kit, users can learn about color & image recognition, intelligent grasping, robot control principle, etc. For Vision & Conveyor Belt Kit and Vision, the robotic arm can sense the distance of materials for identifying, grabbing, and classifying the objects on the belt. Users can easily create simulated industrial applications in this kit, such as color sorting. Users can have deeper learning in machine vision with the Vision & Slide Rail Kit because the robot can track and grab objects through the dynamic vision algorithm in this kit. With the multiple programming environments supported, the vision educational kits are preferred for school or STEM education production line simulation. Moreover, Elephant Robotics also offers different educational programs for students and teachers, to enable them to better understand the principles and algorithms of robot vision, helping them operate these robot kits more easily.

DIY kits

There are two kits in the DIY series: the Drawing Kit and Laser Engraving Kit. Users will enjoyonline production, nameplate and phone case DIY production, and AI drawing with the multiple accessories in the DIY kits.

To help users quickly achieve DIY production, Elephant Robotics created software called Elephant Luban. It is a platform that generates the G-Code track and provides primary cases for users. Users can select multiple functions such as precise writing and drawing, laser engravingwith, only with a few clicks. For example, users can upload the images they like to the software, Elephant Luban will automatically generate the path of images and transmit to ultraArm, then users can choose drawing or engraving with different accessories.

There is no doubt that ultraArm with different robotics kits certainly provides a great deal of help and support to the education field. These kits offer better operating environments and conditions for students, and help them get better learning in robotic programming. Elephant Robotics will continue to launch more products and projects with the concept of helping more users to enjoy the robot world.

Now ordering ultraArm in Elephant Robotics Shop can enjoy the 20% discount with the code: Ultra20

AI Robot Kit 2023 All-around Upgrades: Elephant Robotics aims at Robotics Education and Research

In 2021, Elephant Robotics launched the AI Kit. It is a robotic kit that integrates multiple functions including vision, positioning grabbing, and automatic sorting modules. For people who are new in robotics, AI Kit is a preferable tool to learn the knowledge about machine vision and AI knowledge.

With the continuous advancement of technology, Elephant Robotics has upgraded the AI Kit comprehensively, improving the quality of the hardware while optimizing the built-in algorithms and software to make the product more developable and scalable.

Machine vision is a technology that uses machines to replace the human eyes for target object recognition, judgment and measurement. Machine vision simulates human vision function by computer, and the main technology involves target image acquisition technology, image information processing technology, and target object measurement and recognition technology.

A typical machine vision system mainly consists of a vision perception unit, an image information processing and recognition unit, a processing result display unit and a vision system control unit.

Here we introduce what Elephant Robotics achieve in this upgraded AI Kit 2023.

Textbook and tutorials for robotics

To provide comphrehensive support to experimental and practical teaching, Elephant Robotics launches a textbook about machine vision programming and control. The book provides the knowledge about robotic arms, vision sensors, programming languages, etc. It is a perfect solution for K-12 edication, educational institudes, and colleges. With the help of the tutorials and textbooks, students will enjoy robotics through experiential learning with easier operation when using AI Kit 2023. And Elephant Robotics will launch the tutorials about programming the AI Kit 2023 on YouTube and Hackster continuously.

5 built-in mainstream algorithms

AI Kit 2023 uses eye-to-hand mode, it can achieve color localization by OpenCV, and frames out the colored objects, and calculates the spatial coordinate position of the objects relative to the robotic arm by the relevant point position. With the algorithms, the robotic arm on AI Kit 2023 will automatically recognize the color objects and classify to the corresponding bins.

Aruco codes are widely used to increase the amount of information mapped from the two-dimensional world to three-dimensional time. Elephant Robotics has added recognition algorithms to AI Kit 2023 to support the recognition of 4 different codes. It helps users to learn the related recognition algorithms and positioning applications.

Feature point refers to the ability to represent an image or target in an identical or very similar invariant form in other similar images containing the same scene or target. The feature points are determined by examining the differences between the pixel points and the 16 pixel points in the surrounding field, and the detection efficiency is greatly improved by the segmentation test algorithm.

This algorithm of AI Kit 2023 helps users understand the feature points of images, learn image segmentation, and save image features.

You Only Look Once (YOLO) is a very popular model architecture and object detection algorithm. Elephant Robotics builds this algorithm with the latest version in the AI Kit 2023, the YOLOv5. YOLOv5 makes further improvements on the basis of YOLOv4 algorithm, and the detectability including speed and accuracy are further enhanced. With YOLOv5, users can have a deeper understanding of artificial intelligence, such as the concept and function of neural networks and deep learning.

Shape recognition of objects is an important direction of pattern recognition. There are various representations of object shapes in computers. Based on different shapes, various shape recognition methods have been proposed, such as methods based on Fourier descriptors, principal component analysis, and invariance distance. In shape recognition, it is very important to identify the pattern features on which the recognition is based.

Hardware upgrades

In terms of hardware, AI Kit 2023 adds different sizes of parts boxes to assist the robotic arm to better classify objects. Secondly, AI Kit 2023 used the camera with higher accuracy and lightness adjustment to make the robotic arm more efficient in recognition. Elephant Robotics has also upgraded the suction pump installed at the end of the robotic arm, so that it has higher adaptability and stability when working with different robotic arms.

Software updates

Elephant Robotics develops a built-in visualization software and provides customization methods in the AI Kit 2023. In this software, users can directly select the different algorithms to perform different functions and change the coordinates. The visual interface helps users quickly identify, access and manipulate data, and enables interaction and manipulation in a variety of ways. AI Kit 2023 is more user-friendly now, evern beginner who are new in programming or has no knowledge of code can also use it with several clicks.

Also, Elephant Robotics enhances the adaptations of AI Kit 2023 to enable it to be paired with six robotic arms, including the M5Stack and RaspberryPi versions of myCobot 280myPalletizer 260, and mechArm 270.

Many educational institutions and colleges have already adopted AI Kit 2023 as an educational tool for professional or laboratory use, enabling students to learn to better understand artificial intelligence, robotic programming, and automation. Elephant Robotics is focusing on developing more and better robotics solutions and kits to provide more comprehensive conditions for the technology and education industry and deepen the application of robotics in education and research.

Use Coupon Code „robotsblog“ to get a discount of 8% at https://shop.elephantrobotics.com/