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Robot Programming: What, When, How

Robot programming is a technology practice that’s set to define the next era of human civilization. Robots made a profound impact on numerous sectors in Industry 4.0. Smart automation, IoT devices, big data analytics, virtual and augmented reality, multi-cloud infrastructures, and cyber-physical interactions were some of the primary robot-adjacent advancements in Industry 4.0.

Robots are going to be even more integral in Industry 5.0, which is likely to be the most radical chapter in the human story.

Industry 5.0 will witness the unraveling of complex relationships between robots and human beings. Robots will infiltrate nearly every industry, and the nature and quality of their relationships with human workforces is going to be a defining factor.

This article is a comprehensive introduction to robot programming. It includes robot programming fundamentals, essential skills required for robot programming, current trends, significant challenges, and future trends. 


Robot Programming 101

Robot Programming defined

Robot programming embeds intelligence into machines. It involves writing computer commands that can enable machines to perform certain functions and react to their environments. Robots can be programmed to have varying degrees of autonomy. Some robots are entirely autonomous, others are semi-autonomous, and some pre-programmed robots rely heavily on humans.

McKinsey’s 2022 Global Industrial Robotics Survey reveals that industrial enterprises are set to invest heavily in robotics and automation. 23% of retail and consumer goods sector respondents plan to spend more than $500 million on robotics and automation in the future. 15% of respondents from the life sciences, healthcare, and pharmaceuticals industries and 15% from the food and beverage industry also expect to spend upwards of $500 million on automated robots. This undoubtedly makes robot programming one of the most important capabilities in the world, one that can help businesses of all sizes and from all sectors.

Types of robots and their programming requirements

The end-use application for robots varies across industries. The aforementioned McKinsey survey states that the top 8 use cases for automated robots include:

  1. palletization and packaging,
  2. material handling,
  3. goods unloading and storage,
  4. forklifts,
  5. sorting,
  6. quality assurance,
  7. picking, and
  8. lifting.


There are numerous other use cases and unlimited future potential for the application of robots. Getting acquainted with different types of robots and their programming requirements is important. Here are five key examples.

  • Cobots: Cobots are collaborative robots that work alongside humans in diverse industrial contexts. Cobots have many uses, including machine tending, assembly, quality control, and dispensing. Cobots are relatively easy to program, although some complex older versions require traditional heavy-duty programming. Most cobot programming can be achieved with minimalist drag-and-drop commands that the end user can do.
  • Articulated Robots: These robots feature rotary joints and act as the equivalent of a human arm. Articulated robots feature high levels of precision and therefore require the same precision to be programmed. Programming articulated robots requires a perfect balance between code and the configuration of surrounding physical parameters.
  • Humanoids: Humanoid robots entered the public consciousness through various pop culture portrayals. In reality, they are used in diverse contexts, including entertainment, service, manufacturing, and healthcare. Humanoids require a high degree of onboard data processing for them to mimic organic beings that can respond to their surroundings.
  • Autonomous Mobile Robots (AMRs): These robots can move freely, safely, and autonomously in an environment. They drive operational efficiency in numerous sectors, including healthcare, agriculture, manufacturing, and warehousing. AMRs also require onboard data processing to understand and navigate their surroundings. They often feature cameras and sensors to capture and utilize data about their environment.
  • Automated Guided Vehicles (AGVs): AGVs are similar to AMRs in that they are also mobile. The difference is that AGVs move across a predesigned track in an environment rather than move freely. These robots are useful in manufacturing because they can help move materials quickly, efficiently, and safely. AGVs also feature cameras, sensors, and lasers, and they are taught to follow tracks on the ground with various inputted data.

What programming languages are used to control a robot?

There are over 1500 robot programming languages in the world. A robot programmer must be literate in at least some top programming languages. Python, for instance, is a powerful language for robot programming. It’s relatively lightweight compared to other languages and makes robot programming inclusive and accessible. Programmers can also use Java, which offers numerous APIs that are useful in robotics.

Knowing C and C++ are necessities of the modern world. C and C++ are widely used for robot programming and can be the perfect starting point for newer robot programmers. Other popular robot programming languages include Pascal and Lisp, which are veteran languages, MATLAB, and Microsoft’s.NET.

Different robotics projects demand different programming languages. Every programming language has its advantages and limitations. Some programming languages are perfect for specific types of robots and use cases, and others may have more diverse application potential. The type of robot, the complexity of its behavior, its surroundings, maintenance requirements, scalability, and security needs are some key factors that programmers must consider before choosing a programming language.

Programming paradigms and methodologies

C, C++, Python, .NET, and Java are programming languages with which to write code for robots. However, languages themselves aren’t sufficient for programming robots. Programming paradigms are required. Programming paradigms are essentially methodologies and approaches that programmers can use. It doesn’t focus on languages, which is just one part of the puzzle. Programming paradigms address the overall approach to programming robots.

Programmers can choose any paradigm that might best suit their robotics project. Paradigms are broadly categorized into declarative and imperative. Imperative paradigms, in a robotics context, will focus on how a robot should do things. Declarative paradigms will focus more on end results. Object-Oriented Programming (OOP), Procedural Programming, and Parallel Processing are examples of imperative paradigms. Examples of declarative paradigms include Logic, Constraint, and Functional programming.

What is a “Robot Operating System” (ROS)?

Robot Operating System or ROS is a collection of open-source robotics middleware, including tools, algorithms, drivers, and libraries that programmers can use for their projects. The primary advantage of ROS is that it’s multi-platform, multi-domain, open source, well-reputed, and highly customizable. Leveraging ROS can help programmers and businesses develop robots and rapidly reach the market.

ROS combines developer tools, advanced software stacks, communications protocols, and a gateway to a vibrant global network of businesses, organizations, and individuals working on exciting, cutting-edge robotics projects.

Essential Skills for Robot Programming

There are numerous skills required to program robots. This section highlights the top 3 skills that all robot programmers should possess to innovate in this bustling field and create an impact in their industry.

1. Mathematical and Algorithmic Foundations

Designing and implementing code for robots requires foundational mathematical reasoning skills and algorithmic thinking. Programmers need to be proficient in linear algebra, fundamental calculus, and differential geometry. Programmers also need to possess technical knowledge of algorithms and train themselves to think algorithmically. They need to be well-versed in robotics algorithms, including D*, Focused D*, D* Lit, PRM, Proportional Integral Differential (PID), and Anytime A* Algorithm.

2. Sensor Integration and Data Processing Techniques

Most robots depend on sensors to achieve varying levels of autonomy. GPS (Global Positioning System), Infrared (IR) Transceivers, as well as acceleration, voltage, cameras, laser range, sound, light, and proximity sensors are some examples of sensors used by robots. Robot programmers need to have knowledge and skills in sensor integration. They also need to be skilled in data processing techniques because simply ingesting data doesn’t result in autonomous machines. That data needs to go through a complex lifecycle ranging from raw data input to insights generation and the facilitation of autonomous behavior.

3. Motion Planning and Control

Motion planning and control is one of the most important capabilities that a robot programmer needs to have. Motion planning refers to anatomizing and segmenting an ideal robotic movement into small sections. Motion planning is conducted to optimize a robot’s behavior and mitigate challenges that may arise, either physical or financial, from a robot consistently performing suboptimal movements. Motion control is a critical component of robotics because it ensures that autonomous machines are functioning in a linear, predictable, safe, and precise manner.

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Current Trends In Robot Programming

Integration with AI/ML

The intersections of AI/ML and robotics are sparking exciting innovations. AI/ML and robotics are inherently symbiotic, and advancements in one sector are fueling the other. Robots’ safety, accuracy, and performance are significantly improving with the introduction of AI/ML-powered mechanisms.

Cloud Robotics

Cloud robotics is the fusion of cloud computing, robotics, and various adjacent technologies, including virtual machines, big data analytics, IoT, ML, and advanced data processing. Robots that leverage cloud infrastructures can potentially become more lightweight because they will rely on less hardware.

Swarm Robotics

Swarm robotics involves the unification of large fleets of robots. These fleets could potentially comprise thousands, perhaps even millions, of robots with the same capabilities, controls, and end goal. Potential end-user industries include healthcare, military, manufacturing, and construction. 

Simultaneous Localization and Mapping (SLAM)

SLAM is a powerful technology that enables robots to map new environments and locate themselves on newly constructed maps. SLAM is being explored in surgery-related healthcare contexts, XR media production for entertainment industries, autonomous vehicles, including drones, and even domestic appliances like robot vacuum cleaners.

Human-Centric Robot Programming

Human-centric robots are critical to our future. Human-centric robot programming involves the optimization of robots to enable them to be powerful companions to human workers. Human-centric robot programming is needed to ensure that advancements in robotics and human-robot interactions don’t compromise the safety, efficiency, and experiences of human workforces.

Edge Robotics

The fusion of edge computing and robotics is showing tremendous promise. The narrowing in proximity between IT and OT systems means that robots can ingest, process, and analyze data at the periphery of enterprise networks. This can greatly enhance robot performance and security.

Robot arm's digital twin built by R&D Embedded

Current Challenges and Future Trends in Robot Programming

Advancements in robot programming will transform our world. There is much to look forward to in the next era of robotics. But businesses first need to understand and address a few critical challenges that are affecting robot programming today.

The biggest challenges in robot programming include technical complexity, limitations in robot perception systems, roadblocks in human-robot interactions, scalability, and the ever-present challenge of affordability and rising costs. There are also numerous ethical considerations and challenges that robotics innovators and programmers need to acknowledge and mitigate.

There’s unlimited potential in robotics programming if the challenges mentioned above can be meticulously and responsibly addressed. Future trends and unlockable technologies include seamless human-robot collaboration and interaction, a rise in edge intelligence and distributed robotics, multi-robot systems, swarm intelligence that could profoundly transform enterprises, continual learning and lifelong adaptation capabilities, and the integration of augmented reality (AR) and virtual reality (VR) in robotics. One of the most important future possibilities in robot programming is robots that are implanted with ethical AI.

The scope of robot programming is endless.


Robot programming is a future-defining technological activity. Different robots like cobots, articulated robots, humanoids, AMRs, and AGVs have different requirements that businesses and programmers need to be aware of. C, C++, Python, .NET, and Java are all robust programming languages for robotics but need to be guided by a programming paradigm so that innovations are cohesive, systematic, and logical.

The fundamental skills that robot programmers require include mathematical and algorithmic knowledge, sensor integration and data processing techniques, and motion planning and control. Proficiency in these skills can help programmers contribute to exciting current trends like AI/ML integrations, cloud robotics, swarm robotics, SLAM, human-centric robots, and edge robots. Potential future trends can be unlocked if a series of significant robotics challenges can be mitigated.

There are many companies that provide robot programming services and provide information on how to program a robot. However, the best robot programming solutions come from experts like, who prioritize customization and intricate collaboration to deliver robots that feature multinational quality and efficiency at affordable prices.

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Services & Solutions

  • Robot programming & calibration
  • HDI & PLC development
  • Middleware development
  • Simulation software
  • Digitial twin development
  • App management
  • SW support & maintenance
  • Cost optimization
  • Machine Learning, Deep Learning
  • Virtualization & Cloud
  • Sentiment Analysis
  • IoT Devices & Protocols
  • Wireless Modules
  • BLE Bluetooth Low Energy
  • Device Efficiency
  • Secured Connectivity
  • ARM processors
  • Augmented & Mixed Reality
  • Modified kernels for FaaS
  • Long and Short Range Connectivity
  • M2M Applications

Tools & Frameworks

  • Docker
  • Kubernetes
  • MicroServices
  • FaaS
  • AWS
  • Azure
  • OpenStack
  • OpenVINO
  • OpenCV
  • CUDA
  • AR Core
  • AR Kit
  • Vuforia
  • Unity
  • WebGL
  • Sensors & Actuators

Protocols & Standards

  • NBIoT
  • LTE
  • UMTS
  • GSM
  • LoRaWan
  • SAFe

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