The use of legged robots in non-uniform terrains is a deeply studied subject, as they are capable of performing activities such as exploration, monitoring, and collection in places where other solutions present serious disadvantages. However, most of these robots are too expensive and complex for young researchers and students to develop their algorithms and test them in a standardized model. In contrast, we propose an open-source low-cost quadruped robot that employs a ROS framework to give the learner the necessary tools to develop a basic autonomous robot, capable of mapping its surroundings while avoiding obstacles. This paper presents the details of the whole development process, which includes the motion of the robot, achieved using quadratic optimization and static stability of the center of gravity, a LiDAR-based SLAM system, and path planning using the A∗ algorithm. Simulation and testing show that the robot is capable of successfully achieving the tasks with responsive and natural movements.