Botzo is an open-source, 3D-printable quadruped robot engineered to navigate and interact with its surroundings autonomously. \_\_Designed as an educational platform\_\_, it keeps the total bill of materials below **500 €**, making advanced legged robotics accessible to students, hackers, and research groups alike. Every structural part can be printed on a consumer FDM printer, while off-the-shelf servo motors, an inexpensive STM32 or ESP32 brain, and a minimalist PCB handle the motion and sensing. The result is a lightweight, twelve-degree-of-freedom quadruped that trades exotic hardware for clever mechanical design and open software. Distinctive to Botzo is its **learning-first** approach: instead of hand-tuned gaits, the robot is being taught to walk via reinforcement learning inside a PyBullet simulation that mirrors the real mechanics. Once a robust policy is distilled, it is transferred to the physical bot with almost no re-tuning. The repository already contains the full inverse-kinematics engine, URDF files, Gazebo/ROS2 bringup, and a reward-shaping pipeline so builders can jump straight into experimenting with gait discovery, terrain adaptation, or higher-level navigation stacks. Beyond walking, the frame provides **universal mounting rails** on the back, head, and abdomen that accept standard 2020 extrusion or Maker-beam profiles. This lets users bolt on LiDAR, a robot arm, a camera mast, or extra compute without redesigning the core chassis. All CAD (FreeCAD source + STLs), firmware, and simulation assets are released under **MIT license**, courtesy of the IE Robotics & AI Lab. Whether you need a low-cost research rover, a classroom showcase, or a hackable base for your next swarm, Botzo offers a complete, documented starting point that fits in a backpack and in a tight budget.
Category: Mobile Robots
| Part | Notes | |------|-------| | Servo motors | 12 total (3 per leg); specify model in docs | | 3D printed chassis | PLA/PETG recommended | | 3D printed leg assemblies | Upper and lower leg per leg | | Microcontroller | Raspberry Pi or similar SBC | | Motor driver board | Per servo cluster | | LiPo battery | Powers servos and compute | | M3 hardware | Bolts and nuts for frame assembly |