SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) IN ROBOTICS IS WHEN A ROBOT CONSTRUCTIONS A SET OF GEOMETRICAL FEATURES OF ITS ENVIRONMENT (MAPPING) AND USES SENSING TO ESTIMATE WHERE IT IS RELATIVE TO THOSE FEATURES (LOCALIZATION). FOR EXAMPLE THE ROBOT LEARNS WHERE WALLS ARE IN A BUILDING AND THEN CAN LEARN HOW TO NAVIGATE BETWEEN A START AND GOAL WITHOUT HITTING THEM. MOST PREVIOUS WORK USES LIDAR (3D LASER SENSOR LIKE ON KINECT) OR BI/TRI‐OCULAR (TWO OR THREE IMAGE CAMERAS) SENSORS FOR SOLVING THE SLAM PROBLEM. WE PROPOSE THE USE OF A MONOCULAR SENSOR WHICH IS JUST A SINGLE CAMERA THAT RECORDS IMAGES WITHOUT ANY 3D DATA ALONG WITH AN INERTIAL MEASUREMENT UNIT. USING THE ACCELEROMETER AND GYROSCOPE ALONG WITH THE CAMERA IN A SMARTPHONE IT IS POSSIBLE TO EXTRACT 3‐D INFORMATION ABOUT THE WORLD AND THE ROBOT. BY USING COMPUTER VISION TECHNIQUES THE SETS OF FEATURES ARE FOUND IN A SEQUENCE OF CAMERA FRAMES. FROM THE ACCELEROMETER AND GYROSCOPE DATA THESE ARE THEN FITTED TO STATISTICAL ESTIMATES OF WHERE THESE FEATURES ARE IN THE 3D ENVIRONMENT. THEN USING SENSOR FUSION TECHNIQUES THE DATA IS COMPILED AND THEN TRADITIONAL SLAM ALGORITHMS ARE USED. THIS WOULD ALLOW SLAM WITHIN LOWER WEIGHT COST AND POWER SENSORS. THE SMART SPHERES PROJECT WILL DIRECTLY BENEFIT FROM THE DEVELOPMENT OF THIS MONOCULAR SLAM TECHNIQUE ALONG WITH THE ACCOMPANYING TOOLKIT OF CONTROL AND PLANNING ALGORITHMS. THIS FRAMEWORK WILL ENABLE AUTONOMY WHICH IN TURN WILL LIGHT WEIGHT AND LOW POWER ROBOTS TO AID ASTRONAUTS IN THEIR MISSIONS PARTICULARLY WITH TASKS THAT HAVE TO PERFORMED UNDER RESOURCE AND TIME CONSTRAINTS AROUND THE SPACE STATION. FINALLY THE TECHNOLOGY WILL HAVE DIRECT APPLICATIONS TO SUCH EXPLORATION PROBES AS THE MARS ROVERS WHICH HAVE TOO MUCH OF A COMMUNICATION TIME DELAY TO BE OPERATED PURELY BY TELEOPORATION.