1. Introduction

Mecademic robots are designed to integrate seamlessly into a wide variety of industrial, research, and automation environments. To support this flexibility, we provide multiple programming and communication interfaces, allowing users to choose the level of abstraction, determinism, and integration that best fits their application. The available APIs range from a simple, human-readable TCP/Text interface, to high-performance cyclic fieldbus protocols for deterministic control, as well as a high-level Python API for rapid development and advanced workflows. This section provides an overview of each interface and helps you understand when and why to use them.

1.1. TCP/Text API

The TCP/Text API is the default and most direct way to communicate with a Mecademic robot. It is based on a plain-text command protocol transmitted over a TCP/IP connection. Commands are sent as ASCII strings (e.g., SetBlending(50)) and executed sequentially by the robot controller, with textual responses (e.g., [3012][End of block.]) returned to the client. The general principles of this API are described in Section 3, whereas the available commands are detailed in the Robot commands part of this manual.

This TCP/Text API is particularly well suited for quick setup, debugging, and low-level control. Because the commands are human-readable, it is easy to test interactions using standard tools such as terminal applications or custom scripts. The TCP/Text API exposes most robot functionalities, including motion commands, configuration settings, and status queries.

In addition to standard command sequencing, the TCP/Text interface supports high-frequency streaming of motion commands (allowing for dynamic path generation) and provides access to the robot’s Real-Time Monitoring data feed. While it does not offer the hard real-time determinism of a cyclic fieldbus, it is sufficiently fast for many dynamic control applications, prototyping, and integration with custom software environments.

The TCP/Text API commands are the basis for all other APIs provided by Mecademic, and they are therefore referenced throughout this manual, and particularly in Section 2, where we explain the basic concepts and definitions related to how our robot works, disregarding the API used.

1.2. Cyclic Fieldbus APIs

For applications requiring strict determinism and tight synchronization with external equipment, Mecademic robots support industrial cyclic communication protocols: EtherCAT, EtherNet/IP, and PROFINET. These protocols enable deterministic data exchange between the robot and a PLC or industrial controller.

In cyclic operation, data is exchanged at a fixed rate, allowing the controller to monitor robot states and send commands (such as desired joint positions or velocities) with predictable latency. This makes these APIs well suited for factory automation, machine tending, and applications where the robot must operate in coordination with other motion systems or safety controllers.

Each protocol follows the conventions and tooling of its respective ecosystem, allowing Mecademic robots to be integrated into existing industrial networks with minimal disruption. The way the Cyclic data is related to the TCP/Text commands is explained in Section 4, whereas the specificities of each cyclic protocol are presented in Section 5, Section 6, and Section 7. For each robot command described in the Robot commands part of this manual, we also mention its equivalent in cyclic protocols.

1.3. Python API

The Python API provides a high-level, user-friendly interface for controlling Mecademic robots using the Python programming language. It abstracts the underlying communication details and exposes robot functionality through intuitive classes and methods. The Robot class methods map directly to the TCP/Text API commands, allowing for the use of the same arguments and syntax.

This API is especially valuable for rapid application development, research, and advanced automation workflows. Python’s extensive ecosystem makes it easy to combine robot control with data processing, machine vision, artificial intelligence frameworks, or test automation tools.

Python API documentation is available from the source code, available at our GitHub account.