Cartesian system: a simple alternative robot

Cartesian axis robots can be supplied in the following configurations:

  • Basic supply of axes only, without motors, without sensors and without electrical system
  • Supply as in point 1 plus support frame
  • Supply as in point 1 plus electrical cabinet with PLC (Siemens, Omron or Mitsubishi) or CNC, 7″ colour touch screen operator panel, motors, drives and sensors
  • Delivery as in item 3 plus control and command software

A Cartesian robot, also known as a gantry robot or linear robot, is a type of industrial robot that operates on a Cartesian coordinate system. This system defines positions in three-dimensional space using three perpendicular axes: X, Y, and Z. Cartesian robots are characterized by their linear motion along these axes.

Key features of Cartesian robots include:

  1. Linear Motion: Cartesian robots move along straight paths along the X, Y, and Z axes. This movement is achieved using linear actuators or motors mounted along each axis.

  2. Rectangular Workspace: The workspace of a Cartesian robot typically forms a rectangular shape defined by the range of motion along each axis. This allows for precise positioning within a specific area.

  3. Versatility: Cartesian robots are versatile and can be used in a wide range of applications, including pick-and-place operations, material handling, assembly, packaging, and inspection tasks.

  4. Precision: These robots offer high precision in positioning and repeatability, making them suitable for applications requiring accurate placement of components or objects.

  5. Simplicity: Cartesian robots are relatively simple in design compared to other types of industrial robots, such as articulated robots. This simplicity often translates to easier programming, setup, and maintenance.

  6. Cost-Effectiveness: Due to their simpler design and operation, Cartesian robots can be more cost-effective than other types of industrial robots, especially for applications that do not require complex motion patterns or high-speed operation.

We manufactures a wide range of 2- to 6-axis Cartesian robot for handling objects with masses ranging from 2Kg up to 180Kg with operating areas of up to 20 square metres and with operating volumes of up to 50 cubic metres.

Techical features

LIGHT SERIES: used in assembly systems, subassemblies and painting.
MEDIUM SERIES: used in applications such as case packers, small palletisers, small
automatic warehouses and parts handling.
HEAVY SERIES: used in automatic warehouses, palletisers and for
handling of heavy objects.


An economy version exists for all manipulator models.

Light size manipulators can be supplied with Sanyo stepper motors and RTA drives. Medium and heavy size manipulators can be supplied with asynchronous motors and inverters (solution to be used for lower performance applications). Manipulators with frequency inverters are fitted with Lenze 8400 series HighLine motors and inverters. Thanks to the inverter’s Motion Control Kernel, servo control of the asynchronous motor is possible. The positioning commands are sent to the inverter via the CAN OPEN bus (on board) or with an additional module: Profibus Dp, Profinet, EtherCAT, EtherNet/Ip

We can an supply various models of palletising and depalletising grippers for cartesian robot:

  • One fixed and one movable flap grippers with flap widths of 400 and 800 mm
  • Self-centring flap grippers with flap widths of 400, 800 mm and 1200 mm
  • Pneumatically or electrically operated grippers
  • Box and tray filling grippers
  • Independent multiple grippers with veriable pitch
  • Vacuum gripping units with suction plates
  • Special grippers

Box palletizers

Box palletizers are automated systems used in manufacturing and distribution facilities to stack boxes or other packaging units onto pallets in an organized manner. These systems play a crucial role in material handling and logistics by increasing efficiency, reducing labor costs, and ensuring consistent stacking patterns. Here’s how box palletizers typically work:

Input Conveyor: Boxes or packaged goods are fed into the palletizing system via a conveyor belt or roller conveyor.

Orientation and Alignment: The boxes are usually aligned and oriented properly before they reach the palletizing area to ensure uniform stacking.

Robotic or Mechanical Arms: Box palletizers can employ either robotic arms or mechanical gantries to pick up boxes from the input conveyor and place them onto the pallet.

    • Robotic Arms: These are versatile and can handle various box sizes and shapes. They are equipped with end-of-arm tooling, such as grippers or suction cups, to grasp and lift boxes.

    • Mechanical Arms: These systems typically use fixed or programmable mechanical arms to perform stacking. While less flexible than robotic arms, they can be more cost-effective for certain applications.

    • Pallet Stacking: The palletizer arranges the boxes onto the pallet according to a predefined pattern or configuration. This pattern is often optimized to maximize stability and space utilization.

Layer Formation: Box palletizers can stack boxes layer by layer, adjusting the position and orientation of each box to achieve the desired stacking pattern.

Pallet Handling: Once a layer is completed, the palletizer may lower the pallet to accommodate the next layer or move it to a staging area for further processing.

Pallet Transport: After the pallet is fully loaded, it is typically transported to a stretch-wrapping station or shipping area for storage or transportation.

Logirobotix manufactures Cartesian palletisers, Cartesian robots and scara robots for palletising; together with our own conveyors, we are able to produce complete end-of-line systems. In order to meet customer requirements, we produce customised systems.

The productivity of the palletisers is up to 14 picks per minute. Palletisers made with servomotors or with asynchronous motors and inverters.

To complete the palletiser and end-of-line offer, we can offer a wide range of grippers and palletisers (automatic interlayer positioners) to realise complete end-of-line systems.

High-speed palletiser consisting of a tubular steel frame over which a 3- or 4-axis Cartesian gantry robot moves. Manufactured in 3 versions with 1, 2 or 3 pallet places, it can have a telescopic vertical axis to reduce the vertical footprint. The palletiser is characterised by its high speed and its perimeter completely devoid of mechanical parts. The maximum productivity is 14 grips per minute and the payload is up to 100 kg. Each palletiser version can be supplied with three-phase asynchronous motors and inverters (to realise end-of-line at low cost and performance).

  • Two distinct model groups with both longitudinal and transverse pallet orientation.
  • The models with transverse orientation are made with 1, 2 or 3 pallet places.
  • Possibility of direct pallet and flap gripping.
  • Rotation of the pneumatic gripping element (0-90) or with a 4th axis.
  • Versions with servomotors and productivity up to 14 grippers per minute
  • Low cost versions with asynchronous motors and inverters and productivity up to 8 grippers per minute
  • Telescopic vertical axis for palletising heights over 1500mm.
  • Models with servomotors, controlled by Siemens S7-300 2DP PLC
  • Models with inverter and asynchronous motors controlled by Siemens S7-300 PLC
  • 5.7″ colour touch screen operator panel
  • Powder-coated tubular steel frame
  • Servomotors connected to the PLC with Profibus bus
  • Hardened and ground translation guides with recirculating ball carriages
  • Maximum liftable weight 60Kg – 100Kg including clamp.
  • Maximum palletisable height 1800mm
  • Perimeter protection in powder-coated steel mesh.
  • Pallet exit side protection with light barrier and muting device

Cybersecurity required for safe IIoT robots

Implementing robust cybersecurity measures is crucial for ensuring the safety and security of Industrial Internet of Things (IIoT) robots. Here are some essential cybersecurity practices to consider:

Network Segmentation: Segregate IIoT robot networks from other networks within the industrial environment to contain potential breaches and limit unauthorized access.

Access Control: Implement strong access controls such as role-based access control (RBAC) and multi-factor authentication (MFA) to ensure only authorized personnel can access and control the robots.

Encryption: Encrypt data both at rest and in transit to prevent unauthorized interception and tampering. This includes encrypting communication between robots and control systems.

Secure Protocols: Use secure communication protocols such as TLS/SSL for data transmission and implement secure APIs for interfacing with the robots.

Firmware and Software Updates: Regularly update firmware and software on the robots to patch known vulnerabilities and ensure they are protected against emerging threats.

Authentication and Authorization: Implement strong authentication mechanisms for both users and devices, and enforce strict authorization policies to control access to sensitive resources.

Intrusion Detection and Prevention Systems (IDPS): Deploy IDPS to monitor network traffic for suspicious activities and take automated actions to mitigate potential threats.

Physical Security: Ensure physical security measures are in place to protect IIoT robots from tampering or theft, including secure storage and restricted access to robot control systems.

When dealing with Modbus-enabled robots in an industrial setting, additional considerations specific to the Modbus protocol should be taken into account to ensure cybersecurity. Here are some key points:

Secure Communication: Implement secure communication channels when using Modbus, such as VPNs or secure tunnels, to encrypt data transmitted between devices. This helps prevent eavesdropping and data tampering.

Access Control: Employ access control mechanisms within the Modbus network to restrict access to authorized users and prevent unauthorized access or modifications to robot configurations.

Firewall Protection: Utilize firewalls to filter and control traffic to and from Modbus-enabled devices, ensuring that only legitimate communication is allowed and protecting against unauthorized access attempts.

Authentication and Authorization: Implement strong authentication mechanisms within the Modbus protocol to verify the identity of devices and users before allowing access to robot control functions or data.

Data Integrity Checks: Use checksums or cryptographic hash functions to verify the integrity of data exchanged over the Modbus network, helping to detect any unauthorized modifications or tampering.

Update and Patch Management: Keep Modbus-enabled robots and associated devices up to date with the latest firmware and security patches to address known vulnerabilities and reduce the risk of exploitation.

Intrusion Detection Systems (IDS): Deploy intrusion detection systems to monitor Modbus traffic for suspicious activities or anomalies that may indicate potential security breaches, allowing for timely response and mitigation.

Secure Configuration: Configure Modbus-enabled devices securely, disabling unnecessary services and features, and applying best practices for hardening devices to reduce their attack surface.

Logging and Auditing: Enable logging and auditing of Modbus communications and related events to track and analyze activities, detect security incidents, and support forensic investigations when necessary.

Cyber Attack

Modbus Cyber Attack

IIoT and machine vision enable zero-defect production.

IIoT is increasingly being integrated with industrial robotics to create smarter, more connected manufacturing systems. This integration allows for real-time monitoring, data collection, and analysis, enabling predictive maintenance, optimizing production processes, and improving overall efficiency.

With the proliferation of IIoT sensors and devices, vast amounts of data are being generated in industrial environments. Advanced analytics and artificial intelligence (AI) technologies are being used to derive actionable insights from this data, enabling better decision-making, process optimization, and predictive maintenance in industrial robotics systems.

The integration of IIoT (Industrial Internet of Things) and robotics is a pivotal trend in industrial automation, revolutionizing manufacturing processes across various sectors. Here are key aspects of this integration:

Real-time Monitoring and Data Collection: IIoT sensors are embedded within robotic systems to monitor various parameters such as temperature, pressure, speed, and position in real-time. This data is collected and transmitted to centralized systems or cloud platforms for analysis.

Predictive Maintenance: By analyzing the data collected from IIoT sensors, predictive maintenance algorithms can anticipate potential failures or issues in robotic systems. This allows for proactive maintenance scheduling, minimizing downtime and optimizing productivity.

Optimized Production Processes: IIoT-enabled robotics facilitate dynamic process optimization by adjusting parameters in real-time based on the data received. For instance, robotic arms in manufacturing assembly lines can adjust their speed or trajectory based on feedback from sensors to improve efficiency and quality.

Quality Control and Inspection: IIoT sensors integrated with robotic systems enable continuous quality monitoring and inspection during the manufacturing process. Robots equipped with vision systems and other sensors can detect defects or anomalies in products, allowing for immediate corrective actions.

Supply Chain Visibility: IIoT-connected robotics provide visibility into the entire supply chain by tracking the movement of raw materials, work-in-progress inventory, and finished goods. This transparency enables better inventory management, logistics optimization, and demand forecasting.

Enhanced Safety: IIoT sensors enhance safety in industrial environments by monitoring environmental conditions and detecting potential hazards. For example, robotic systems can be equipped with proximity sensors to detect the presence of humans or obstacles and adjust their behavior accordingly to prevent accidents.

Remote Monitoring and Control: IIoT connectivity enables remote monitoring and control of robotic systems from anywhere with an internet connection. This capability allows operators to oversee multiple robotic installations, troubleshoot issues remotely, and make real-time adjustments to production processes.

Data-driven Decision Making: The integration of IIoT with robotics generates vast amounts of data that can be analyzed to derive actionable insights. Data analytics tools and machine learning algorithms can uncover patterns, trends, and correlations in the data, enabling data-driven decision-making for process optimization and continuous improvement.

Computer Vision and Robotics

Computer vision plays a crucial role in pick-and-place robotics, where robots are tasked with identifying objects in a workspace and accurately picking them up to place them in a designated location. Here’s how computer vision is integrated into pick-and-place robotics:

Object Detection and Recognition: Computer vision algorithms are used to detect and recognize objects within the robot’s field of view. This involves analyzing images or video feeds captured by cameras mounted on the robot or within the workspace. Convolutional Neural Networks (CNNs) are commonly used for object detection tasks, allowing the robot to identify objects based on their shape, color, texture, or other visual features.

Pose Estimation: Once an object is detected, the robot needs to determine its position and orientation in 3D space relative to its own coordinate system. Pose estimation algorithms are employed to calculate the precise pose of the object, enabling the robot to plan and execute its pick-and-place actions accurately.

Grasping Strategy: Computer vision helps the robot determine the optimal grasping strategy based on the shape, size, and orientation of the object. By analyzing the object’s geometry and surface properties, the robot can select the most suitable gripper configuration and approach angle to ensure a secure grasp.

Obstacle Avoidance: Computer vision enables the robot to detect and avoid obstacles in its path, ensuring safe and collision-free operation during pick-and-place tasks. By continuously monitoring the environment using cameras or depth sensors, the robot can adjust its trajectory to navigate around obstacles and reach its target efficiently.

Quality Inspection: In addition to pick-and-place actions, computer vision can be used for quality inspection purposes. The robot can inspect objects for defects, anomalies, or deviations from the desired specifications before picking them up or after placing them in the designated location. This ensures that only high-quality products are processed and delivered downstream.

Adaptive Behavior: Computer vision allows the robot to adapt its behavior in real-time based on changes in the environment or the objects being handled. For example, if the lighting conditions change or new objects are introduced into the workspace, the robot can dynamically adjust its perception and manipulation strategies to maintain performance and reliability.

Integration with Robot Control: Computer vision systems are tightly integrated with the robot’s control system to enable seamless interaction and coordination between perception and action. This integration allows the robot to receive real-time feedback from the vision system and adjust its movements accordingly to achieve precise pick-and-place operations.