What are the different types of robot control systems?


Robot control systems are the brains behind robots, allowing them to perceive, plan, and execute actions in the real world. They encompass a wide range of technologies, from low-level motor control to high-level artificial intelligence, and play a crucial role in developing and applying robots across various industries.

A typical robot control system consists of several fundamental components that work together in a coordinated manner to achieve desired robotic behaviors. These components include sensors, actuators, controllers, and software.

1. Sensors

Sensors are the eyes and ears of a robot, providing it with information about its environment. They gather data about various aspects of the robot’s surroundings, such as:

  • Position and orientation: Sensors like encoders and gyroscopes measure the robot’s position and orientation in space, allowing it to determine its location and track its movements.
  • Forces and pressures: Force and pressure sensors detect environmental interactions, enabling the robot to grasp objects with the right force or avoid obstacles.
  • Vision and touch: Cameras and tactile sensors provide visual and tactile information, allowing the robot to perceive objects, shapes, and textures.

2. Actuators

Actuators are the muscles of a robot responsible for its movement. They convert energy into physical motion, enabling the robot to perform actions such as:

  • Joint movements: Motors and servos control the rotation of joints in the robot’s arm or manipulator, allowing it to reach, grab, and manipulate objects.
  • Locomotion: Wheels, tracks, or other locomotion devices enable the robot to move around its environment, navigating from one location to another.
  • Gripping and manipulation: End effectors, attached to the end of the robot’s arm, can be equipped with actuators to grip objects, apply force, or perform specific tasks.

3. Controllers

The controller is the brain, responsible for analyzing sensor data, making decisions, and sending commands to the actuators. It determines how the robot should react to its environment and executes the necessary actions.

  • Low-level control: Low-level controllers handle basic motor control, ensuring accurate and precise movements of individual joints or actuators.
  • High-level control: High-level controllers coordinate multiple actuators and sensors, planning complex motions and adapting to changing environments.
  • Artificial intelligence: Artificial intelligence algorithms are increasingly being incorporated into robot controllers, enabling them to learn, make decisions, and autonomously perform tasks.

4. Software

Software provides the overall framework for the robot control system, including communication protocols, data management, and user interfaces. It integrates various hardware components and control algorithms, making the robot a cohesive and functional system.

  • Real-time operating systems (RTOS): RTOS provides efficient scheduling and resource management for real-time control tasks, ensuring timely responses to sensor inputs and actuator commands.
  • Middleware: Middleware facilitates communication between software components, allowing seamless data exchange and control signal transmission.
  • User interfaces: User interfaces allow humans to interact with the robot, setting tasks, monitoring performance, and adjusting parameters.

The interaction between these fundamental components enables a robot to perceive its surroundings, make decisions, and execute actions in a coordinated manner, fulfilling its intended purpose and achieving desired behaviors.

Types of Robot Control Systems

Robot control systems can be classified into different categories based on their level of autonomy and the nature of the tasks they perform. Some common types include:

1. Open-Loop Control

Open-loop control systems do not use feedback from the robot’s environment to adjust their actions. They rely on predefined commands and assume a predictable environment. These systems are typically simpler to implement and less expensive, but they are also less accurate and adaptable to changing conditions.

Examples of Open-loop control systems include Conveyor belts and Automated sprinklers. Conveyor belts rely on a fixed speed and direction, assuming that objects will be placed correctly and move smoothly along the conveyor. Automated sprinklers follow a predetermined schedule and water distribution pattern, assuming the lawn or garden has a uniform shape and requires consistent watering.


  • Simple and inexpensive to implement
  • Suitable for predictable environments and repetitive tasks


  • Less accurate due to lack of feedback
  • Less adaptable to changing conditions

2. Closed-Loop Control

Closed-loop control systems incorporate feedback mechanisms to monitor the robot’s performance and make necessary adjustments. This allows for more accurate and adaptive behavior in dynamic environments. Sensors measure the robot’s output and compare it to the desired output, generating an error signal. The controller then uses this error signal to adjust the robot’s actions, reducing the error and achieving the desired outcome.

Examples of Closed-Loop Control include Robotic manipulators and Self-driving vehicles. Robotic manipulators use feedback from joint encoders and force sensors to ensure precise positioning and controlled movements. Self-driving vehicles use a variety of sensors, including cameras, radar, and lidar, to gather real-time information about their surroundings and adjust their path accordingly.


  • More accurate and reliable performance
  • Adaptable to changing environments and disturbances
  • Capable of handling complex tasks


  • More complex to design and implement
  • Requires additional sensors and feedback mechanisms

3. Reactive Control

Reactive control systems respond directly to sensory inputs, making them suitable for tasks that require quick reflexes and adaptation to real-time changes. These systems typically do not have internal models or planning capabilities, but they can still achieve complex behaviors by reacting to immediate stimuli.

Examples of Reactive Control include insect-inspired robots and Reflex-based robots. Insect-inspired robots use simple sensors and reactive control algorithms to navigate complex environments and avoid obstacles. Reflex-based robots respond to sudden changes in their surroundings, such as falling objects or obstacles, by evasive actions.


  • Fast response times
  • Adaptable to unpredictable environments
  • Suitable for reactive tasks


  • Limited planning and decision-making capabilities
  • Not suitable for tasks requiring long-term planning or goal-oriented behavior

4. Deliberative Control

Deliberative control systems use internal models and planning algorithms to generate high-level actions. They are well-suited for complex tasks that require reasoning, decision-making, and long-term planning. These systems often incorporate knowledge representation, path planning, and optimization techniques to achieve their goals.

Examples of deliberate control include robotic surgeons and autonomous exploration robots. Robotic surgeons use preoperative planning and real-time feedback to perform delicate surgical procedures accurately. Autonomous exploration robots use internal maps and planning algorithms to navigate unknown environments, collect data, and decide their exploration path.


  • Capable of complex planning and decision-making
  • Suitable for long-term tasks and goal-oriented behavior
  • Can handle uncertainty and incomplete information


  • Computationally demanding
  • Requires accurate internal models and planning capabilities
  • Maybe less reactive to immediate stimuli

The choice of a robot control system depends on the specific task, the environment, and the desired level of autonomy. Open-loop control is suitable for simple tasks in predictable environments, while closed-loop control provides more accuracy and adaptability. Reactive control is well-suited for tasks requiring quick reflexes, while deliberative control is ideal for complex planning and decision-making tasks.

Top manufacturers of robot control systems

Here are some of the top manufacturers of robot control systems:

ABB Robotics

ABB is a global leader in robotics and automation, with a wide range of robot control systems for industrial, commercial, and consumer applications. Their products are known for their reliability, accuracy, and ease of use.

Name: ABB IRC5
Specifications: Payload: Up to 350 kg, Reach: Up to 3.21 m, Speed: Up to 2.5 m/s, Accuracy: Up to ±0.05 mm

Bosch Rexroth

Bosch Rexroth is another major player in the robotics industry, offering a comprehensive portfolio of robot control systems for a variety of applications. Their products are particularly well-suited for high-precision and high-performance applications.

Name: Rexroth IndraControl
Specifications: Payload: Up to 1,300 kg, Reach: Up to 7.1 m, Speed: Up to 6 m/s, Accuracy: Up to ±0.1 mm

Siemens Robotics

Siemens is a global technology powerhouse with a strong presence in the robotics industry. Their robot control systems are known for their advanced technology and integration with other Siemens automation products.

Name: Siemens Sinumerik
Specifications: Payload: Up to 1,200 kg, Reach: Up to 6 m, Speed: Up to 5 m/s, Accuracy: Up to ±0.1 mm

Yaskawa Motoman Robotics

Yaskawa Motoman is a Japanese robotics manufacturer known for its high-quality and innovative robot control systems. Their products are used in various industries, including automotive, electronics, and food and beverage.

Name: Yaskawa Motoman DX1000
Specifications: Payload: Up to 1,200 kg, Reach: Up to 3.1 m, Speed: Up to 5.5 m/s, Accuracy: Up to ±0.05 mm

Fanuc Robotics

Fanuc is a world-leading manufacturer of industrial robots and robot control systems. Their products are known for their reliability, durability, and high performance.

Name: Fanuc R-30iA
Specifications: Payload: Up to 300 kg, Reach: Up to 3.1 m, Speed: Up to 5.5 m/s, Accuracy: Up to ±0.05 mm

Denso Robotics

Denso is a Japanese automotive supplier and a major player in the robotics industry. Their robot control systems are particularly well-suited for automotive applications.

Name: Denso VP6200
Specifications: Payload: Up to 600 kg, Reach: Up to 3.7 m, Speed: Up to 5 m/s, Accuracy: Up to ±0.1 mm

Kuka Robotics

Kuka is a German robotics manufacturer known for its high-performance and innovative robot control systems. Their products are used in various industries, including automotive, aerospace, and logistics.

Name: Kuka KR500
Specifications: Payload: Up to 500 kg, Reach: Up to 3.1 m, Speed: Up to 5.5 m/s, Accuracy: Up to ±0.05 mm

Kawasaki Robotics

Kawasaki is a Japanese manufacturer of industrial robots and robot control systems. Their products are known for their high quality and reliability.

Name: Kawasaki RS008
Specifications: Payload: Up to 800 kg, Reach: Up to 3.5 m, Speed: Up to 4.5 m/s, Accuracy: Up to ±0.1 mm

Mitsubishi Electric Automation

Mitsubishi Electric Automation is a Japanese manufacturer of industrial automation products, including robot control systems. Their products are known for their reliability and ease of use.

Name: Mitsubishi Electric R-J7iA
Specifications: Payload: Up to 700 kg, Reach: Up to 3.1 m, Speed: Up to 5.5 m/s, Accuracy: Up to ±0.05 mm

Staubli Robotics

Stäubli is a Swiss manufacturer of industrial robots and robot control systems. Their products are known for their precision and high performance.

Name: Stäubli TX60
Specifications: Payload: Up to 60 kg, Reach: Up to 1.8 m, Speed: Up to 5 m/s, Accuracy: Up to ±0.1 mm