This paper introduces the Stoch BiRo, a cost-effective bipedal robot designedwith a modular mechanical structure having point feet to navigate uneven andunfamiliar terrains. The robot employs proprioceptive actuation in abduction,hips, and knees, leveraging a Raspberry Pi4 for control. Overcomingcomputational limitations, a Learning-based Linear Policy controller managesbalance and locomotion with only 3 degrees of freedom (DoF) per leg, distinctfrom the typical 5DoF in bipedal systems. Integrated within a modular controlarchitecture, these controllers enable autonomous handling of unforeseenterrain disturbances without external sensors or prior environment knowledge.The robot's policies are trained and simulated using MuJoCo, transferringlearned behaviors to the Stoch BiRo hardware for initial walking validations.This work highlights the Stoch BiRo's adaptability and cost-effectiveness inmechanical design, control strategies, and autonomous navigation, promisingdiverse applications in real-world robotics scenarios.