Mars Surface Construction

 Mars Surface Construction


#ISPP #InsituPropellantProduction #ISRU
#InSituResourceUtilization #mars #marsexploration #autonomoussystems #automation #civilengineering #civilengineeringdesign #roboticconstruction #robotics

After the successful flight of the Starship, Mars missions in the transfer orbit windows are much more real than a year ago. Early uncrewed starship missions to Mars will need to establish infrastructure for human exploration. SpaceX will focus mostly on the cargo delivery part. Some of the payloads might need to be ready for the 2024 launch window. 

The need for robotic in-situ resource use is essential.  This discussion should support the process of creating specifications, designs, and simulations of crucial systems.  Eventually, the goal is to develop prototypes - proof of concept cyber-physical systems that can be tested on Earth.

There is a rather significant interest in research and engineering communities, which resulted in papers, conference presentations, simulations, and other early proof of concept work. 

At this point, the main topics of interests are:

-          Software: from construction scheduling to autonomous AI

-          Robotics systems, vehicles, specialized tooling

-          Assembly processes of payload elements

o   Energy sources,

o   ISPP (In-situ Propellant Production), ISRU (In-Situ Resource Utilization) equipment

o   Power grid development,

o   fuel storage)

-          In-situ material acquisition processes 


The Construction Industry and Mars

https://www.linkedin.com/feed/update/urn:li:activity:6743662480142209024

The construction industry is increasingly using automation for the hard labor that goes into construction. There are many reasons, e.g., labor shortages, the dangerous nature of work, and economic pressures, to name only a few.

There is an additional reason for automation to become increasingly important. It is related to the successful Starship demo flight by SpaceX.

After the successful flight of the Starship, Mars missions in the transfer orbit windows are much more real than a year ago. Early uncrewed starship missions to Mars will need to establish infrastructure for human exploration. SpaceX will focus mostly on the cargo delivery part. Some of the payloads might need to be ready for the 2024 launch window. 

The need for robotic in-situ resource use is essential.  This discussion should support the process of creating specifications, designs, and simulations of crucial systems.  Eventually, the goal is to develop prototypes - proof of concept cyber-physical systems that can be tested on Earth.

Source: https://fortune.com/2019/11/23/construction-industry-robots-ai/

 Such companies as Build Robotics, Toggle, Doxel, Dusty Robotics, EKSO Bionics, or FBR offer automated construction systems. Are they going to participate in the early Mars projects? Those projects will need to build essential infrastructure on Mars in the following broad areas:

-          Power generation and power grid

-          Resource acquisition processes, i.e., ISRU (In-Situ Resource Utilization)

-          Propellant production

-          Energy storage

-          Robotic equipment maintenance

These are the essential areas before humans arrive on the red planet. The fuel necessary for the return trip has to be produced on Mars. Fuel production is a very power-intensive process that requires significant mining capabilities to reach the key raw material - water stored underground. The good news is that all elements needed to produce the propellant (methane and oxygen) are on Mars. The science of how to do it has been demonstrated and it works.

Now all the R&D has to be delivered to Mars and put together…

























Piano Mover's Problem: Problem Solving Algorithms for Autonomous Robotics 

The Piano Mover's problem involves planning, understood as a class of algorithms in the field of AI and control theory. In addition to sensing, servo Piano Mover's Problem: Problem Solving Algorithms for Autonomous Robotics 

The Piano Mover's problem involves planning, understood as a class of algorithms in the field of AI and control theory. In addition to sensing, servo control, etc., planning is about translating high-level task specifications to a low-level sub-task solution through a chain of actions. Many other considerations make autonomy hard, e.g., differential constraints, uncertainty, and optimality, to name only a few. Trajectory planning usually refers to the problem of obtaining the solution from a robot motion planning algorithm and determining how to move along the path in a way that respects the mechanical limitations of the robot and the cargo. This excellent paper discusses cylindrical algebraic decomposition (CAD). This particular planning version focuses on autonomous solving the path planning problems for thin, elongated objects moving through narrow corridors. We can think of so many applications in the off-world situation. Currently, I'm adding this implementation based on the cylindrical decomposition to the library of solutions. The architecture is similar to typical machine learning enterprise solutions, where a "tournament" of algorithms is applied to solve a problem.

Similarly, in path planning, competing algorithms (or parameter setup) work best in specific circumstances. However, the configuration space of the meta-level algorithm for unknown conditions on other planets is a bit of a challenge. Therefore, an ensemble or "tournament" approach is probably the way to go until a significant training and test data set can be obtained.   

https://arxiv.org/pdf/1309.1588.pdf #controlsystems #controltheory # #machinelearning #ai #robotics #planning #cylindricalalgebraicdecomposision #algorithms -level





task specifications to a low-level sub-task solution through a chain of actions. Many other considerations make autonomy hard, e.g., differential constraints, uncertainty, and optimality, to name only a few. Trajectory planning usually refers to the problem of obtaining the solution from a robot motion planning algorithm and determining how to move along the path in a way that respects the mechanical limitations of the robot and the cargo. This excellent paper discusses cylindrical algebraic decomposition (CAD). This particular planning version focuses on autonomous solving the path planning problems for thin, elongated objects moving through narrow corridors. We can think of so many applications in the off-world situation. Currently, I'm adding this implementation based on the cylindrical decomposition to the library of solutions. The architecture is similar to typical machine learning enterprise solutions, where a "tournament" of algorithms is applied to solve a problem.

Similarly, in path planning, competing algorithms (or parameter setup) work best in specific circumstances. However, the configuration space of the meta-level algorithm for unknown conditions on other planets is a bit of a challenge. Therefore, an ensemble or "tournament" approach is probably the way to go until a significant training and test data set can be obtained.   

https://arxiv.org/pdf/1309.1588.pdf #controlsystems #controltheory # #machinelearning #ai #robotics #planning #cylindricalalgebraicdecomposision #algorithms

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