ECE.35 – Pysche-16 : Exploration Autonomy

• Dillon Aguilar
• Tanishq Mathur
• Samprithi Vilvasigamani

As humanity ventures further away from Earth to other celestial bodies of wonder in search of an explanation of the origin of the universe, the means of effectively exploring vast celestial surfaces is an imperative consideration. There is no doubt that space is expansive and with any expedition we must consider the delay of instruction signals for the robot to be responsive to the environment. Therefore, machine learning has enabled robotics navigation solutions to perceive an environment similar to how a person may observe their surroundings, through vision. Hence through the use of stereo vision and SLAM (simultaneous localization and mapping), two cameras can map the rover’s surroundings in real time and keep track of any hazards that prohibit the success of its mission. The targeted body of interest is Psyche-16, a hypothesized incomplete planet with a metallic surface estimated to be worth $10 trillion. On Psyche-16, the rover will utilize its stereo vision to determine the ideal path to traverse the surface and survey the surface for future missions, facing unfamiliar terrain and extreme environmental complications. Our prototype can successfully manage to autonomously traverse while collecting information regarding the environment of the surroundings which includes data from our temperature sensor and IMU installed on the rover itself.