Analysis of Popular Robotics Programming Languages: Strengths and Weaknesses
Robotics programming languages first emerged in the early 1970s. Since then, many programming languages have been adopted for robotics development. A common question from beginners is: Which programming language is best for robotics? Unfortunately, there is no single correct answer. Different practitioners will give different recommendations. For robotics engineers and researchers, the most important capability is building computational/programming thinking, rather than judging everything by a single language. In many cases, the specific language matters less than continuously improving your skills through disciplined problem solving and software engineering.
With that context, this article introduces five mainstream programming languages commonly used in robotics R&D and provides a technical comparison of their advantages and limitations.
Python plays an important role in robotics research. One key reason is that Python (together with C++) is one of the primary programming languages in ROS. Like Java, Python is interpreted, but unlike Java it focuses strongly on usability and rapid development.
1. Easy to Learn
Python syntax is simple and readable. Beginners can start quickly, yet the language can scale to complex systems. Development efficiency is high, supported by powerful third-party libraries.
2. High-Level Language
When writing Python programs, you generally do not need to handle low-level concerns such as manual memory management.
3. Portability
Due to its open-source nature, Python has been ported to many platforms. If you avoid OS-dependent features, most Python code can run on almost any system without modification.
4. Extensibility
Performance-critical code can be implemented in C/C++and then integrated into Python, which also helps protect proprietary algorithms.
1. Slower Runtime Performance
Python runs significantly slower than C and is often slower than Java.
2. Limited Multi-CPU Utilization in Threads
This is one of the most commonly cited drawbacks (typically associated with limitations of Python threading in CPU-bound workloads).
C++ evolved from C and is an object-oriented language that inherits many of C’s strengths. Many consider C and C++ a strong foundation for robotics engineers because much of the hardware ecosystem is built on these languages, they support real-time performance requirements, and they are mature and widely deployed.
1. Strong Cross-Platform Support
C/C++ runs on nearly all modern processors and is supported by most operating systems.
2. High Execution Efficiency
C is compact and close to assembly in performance. C++ adds object-oriented capability while maintaining high efficiency and improved code structure.
3. Concise and Flexible; Low-Level Control
C/C++ provides rich operators and data types, direct memory access, and bit-level operations, enabling precise hardware-level control and generating high-quality compiled code.
1. No Garbage Collection
Compared with Java, C/C++ does not provide automatic garbage collection, which increases the risk of memory leaks.
2. Harder to Learn
From an application perspective, C is more difficult than many high-level languages and requires stronger programming fundamentals.
3. Weaker Data Safety
A key limitation is weaker encapsulation (especially in C), which can reduce data safety and increase the likelihood of bugs—also a major difference between C and C++ in practice.
Java syntax is similar to C++. In some sense, Java evolved from C/C++ design concepts. Like C# and MATLAB, Java uses a virtual-machine execution model: it is not compiled directly into machine code; instead, the JVM (Java Virtual Machine) interprets and executes instructions at runtime. In theory, this enables strong portability across different machines. In practice, it can introduce overhead and slower execution in some cases, but Java remains popular in robotics research.
1. Easy to Learn
Java is relatively easy for developers familiar with C/C++ syntax.
2. Supports Dynamic Binding
Java fully supports dynamic binding, while C++ primarily uses it through virtual functions.
3. Supports Internet Application Development
Java provides strong network libraries (e.g., java.net) including URL handling, Socket, ServerSocket, etc.
4. Improved Security
Java includes built-in security mechanisms designed to reduce the risk of malicious code attacks.
5. Portability
Java’s platform-independence comes from its architecture-neutral bytecode and strictly defined primitive type sizes.
1. Requires the JVM
Java applications require a Java runtime environment, which can limit adoption in certain deployment scenarios.
2. Higher Runtime Overhead
Historically, Java could be slow on low-performance hardware. This has improved significantly with modern JVMs and faster computing platforms.
C#/.NET is largely associated with Microsoft’s robotics development ecosystem. For example, Microsoft Robotics Developer Studio used C# as a primary language. If a project adopts that framework, C# is typically required.
1. Powerful .NET Framework Managed Libraries
Provides a broad set of packaged components: file system, UI, data access, networking, COM interop, graphics/multimedia (including WPF). Missing capabilities can often be accessed via Windows APIs.
2. Simplified Language Features
Automatic memory management, single inheritance, plus language features such as events, delegates, properties, and LINQ that simplify application development.
3. Fast Web Application Development
Strong framework and tooling support, UI controls, event-driven development, ADO.NET data access, XML/network libraries, and Windows services.
4. IL + CLR + JIT Execution Model with Good Performance
Code compiles into Intermediate Language (IL), runs under the CLR, and is JIT-compiledinto machine code at runtime. Caching of compiled code improves performance.
5. Code Security
Windows role-based security plus .NET code-access security. Type safety in IL enables the CLR to validate code and enforce permissions before execution.
1. Not Ideal for Low-Level or Extreme High-Performance Workloads
Compared to native C/C++, IL and runtime compilation introduce overhead, and garbage collection makes immediate memory release harder—reducing suitability for strict timing or memory-control requirements.
2. Limited Support Outside Windows (Historically)
Mono and other cross-platform options exist, but maturity and ecosystem coverage may be weaker than Java/Python in many non-Windows environments.
MATLAB and open-source alternatives (e.g., Octave) are widely used for robotics research tasks such as data analysis and control system development. MATLAB also provides a well-known Robotics Toolbox. If you need to process experimental data, generate advanced plots, or design control systems, MATLAB is often a practical choice.
1. High Development Efficiency
MATLAB is designed for mathematical and scientific computing, making it easy to learn and efficient for rapid algorithm development.
2. Strong Matrix and Array Operations
Provides native operators for arithmetic, relational, logical, conditional, and assignment operations, and these translate naturally to array/matrix computations.
1. Low Efficiency for Loop-Based Computation
MATLAB variables are vector-based. Vectorized operations can be very fast, but scalar element-by-element loops are less efficient and more complex.
2. Weak Encapsulation
Variables exist in a shared workspace and can be accessed by any statement. In addition, turning algorithms into complete software products often requires significant additional effort for UI and software structure design.
These five languages are among the most commonly used in robotics programming, but that does not mean developers must master all of them. The key is choosing a language that feels natural, fits your robot hardware and software stack, and enables fast onboarding and development. For beginners, Python is often recommended due to its readability, strong library ecosystem, and broad adoption in robotics development.
Keywords: Service Robot,Usage Guidelines
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