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A robot mining system was developed by the State Space Robotic undergraduate student design team from Mississippi State University (MSU) for the 2016 NASA Robotic Mining Competition. The mining robot was designed to traverse the Martian chaotic terrain, excavate a minimum of 10 kg of Martian regolith and deposit the regolith into a collector bin within 10 minutes as part of the competition. A Systems Engineering approach was followed in proceeding with this design project. The designed mining robot consisted of two major components: (1) mechanical system and (2) control system. This paper mainly focuses on the design and assessment process of the mechanical system but will also briefly mention the control system so as to evaluate the designed robotic system in its entirety. The final designed robot consisted of an aluminum frame driven by four motors and wheels. It utilized a scoop and lifting arm subsystem for collecting and depositing Martian regolith.

The ability to quickly and automatically evaluate vehicle designs is a critical tool in an efficient vehicle design process. This paper presents techniques for vehicle parameter estimation using automatic intelligent simulations. These techniques enable the efficient and automatic evaluation of many important aspects of vehicle designs. The effectiveness of this approach is demonstrated by using vehicle tests that are commonly performed on military ground vehicles. Our simulation techniques are able to determine the relevant vehicle performance characteristics in a much more efficient manner than could be done previously. This is done automatically, once the user has specified the type of test to be performed. A terrain sample is automatically generated and the vehicle’s behavior on each terrain instance is evaluated until the specified test conditions are met.