Here's how you can ace discussing programming languages for Robotics in an interview.

In order to solve difficult robotics problems, an understanding of algorithms has been essential. For instance, we employed pathfinding algorithms like A* to plan paths and avoid obstacles when creating an autonomous navigation system for a robot. With this fundamental understanding, we were able to put into practice workable ideas that greatly increased the robot's efficiency. You create a solid basis for more complex robotics programming subjects by grasping these fundamentals. A thorough understanding of variables, control structures, data kinds, and algorithms is crucial for applying control systems and creating algorithms for autonomous robots.

Through my dedication to robotics research, I have perfected my skills in C/C++ programming. My expertise in C and advanced C empowers me to debug effectively and confront intricate challenges with confidence. By remaining abreast of emerging trends, I consistently demonstrate technical proficiency and adaptability, positioning myself at the forefront of the field.

At work, once... I worked on a project to create an industrial robot's real-time control system. We selected C because of its low-level hardware manipulation capabilities, which let us maximize the robot's responsiveness and performance. We used object-oriented programming in C++ to control the intricate system. Our code is now modular and manageable thanks to this technique, which also makes upgrades and debugging simpler. We were able to attain the real-time performance needed for the robot's tasks by utilizing the advantages of both languages.

As controllers are becoming compact and computationally capable to do the complex task on board, Python is gradually becoming first choice for Programmers associated to Robotics. The options for complex mathematical calculations and algorithms looks way easy to code than doing it in different languages. As ML as well as AI and it's related applications like crewAI and GenAI coming into trends more people started taking interest into Python for robotics applications. Python is easy to understand as we all know and it's straight upwards 📈growing day by day and tools like ChatGPT, Gemini, etc. are available openly, coders can take advantage to learn as well as create new libraries and hardware related programs for python community.

Using Python's many libraries, such as ROS (Robot Operating System) and OpenCV, has shown to be beneficial. These libraries include pre-built features that speed up development considerably. For instance, I recently worked on a project where I integrated different robotic system components using Python. I used ROS to handle sensor and actuator connection, and OpenCV was used for computer vision tasks. Rather than having to start from scratch, this method allowed me to concentrate on higher-level tasks like building machine learning algorithms.

According to my observations, ROS makes it easier to create interoperable nodes, which can be built in Python and C++ among other programming languages. For example, I utilized ROS to control communication between different sensors and actuators in a recent project. I made sure that data was exchanged between components without a hitch by utilizing ROS's powerful messaging mechanism. In addition, I considerably decreased the amount of time needed for debugging and increased system dependability by using ROS to model robotic behavior prior to actual deployment. This framework greatly facilitated the development and integration of the many components of the robotic system.

Using Java because of its portability and user-friendliness has shown to be beneficial, particularly in systems that emphasize distributed or networked intelligence. For instance, Java made cross-platform communication and integration easier in a project centered on networked robotic systems. Furthermore, for mathematical modeling and simulation in robotics, languages like MATLAB are essential. In a different project, I simulated robotic dynamics and kinematics using MATLAB, which aided in the design and optimization of the robotic system prior to its actual deployment. This Java and MATLAB combo offered a solid foundation for robotics development and simulation.