After ensuring a strong enough structure and sufficient current to power the motors, efforts were dedicated to refining the walk cycle of a single leg. Until this point, legs moved along predefined coordinates defined manually, making the movements quite clucky. I decided to avoid inverse kinematics calculations to reduce processing time and resources: this should leave more available memory to the RPi4 for Computer Vision tasks. So, I preferred using forward kinematics, finding a relation between the angles and end effector of the legs. I decided to make the end effector move along a precisely defined curve. This curve comprises two interconnected segments: the upper curve (a), similar (but not) a parabola, and its counterpart below (b), completing a seamless loop.
One of the standout features of this approach lies in its adaptability. The parameters of the functions governing the two curves can be fine-tuned, allowing for the creation of diverse step shapes. Whether it's a stable, measured gait or a more dynamic stride, adjusting these parameters provides versatile options. Furthermore, the execution speed of each step is a customizable element, adding another layer of control to the robot's locomotion.