SG-Lib: Solid Geometry Library Toolbox
The SG-Lib ist a tool for the use of generative AI during the automatic design of robots. The library has been developed since 2010 at the TU Munich, Germany.Generative AI in the construction of robots offers several advantages that can revolutionize the field of robotics:
- Design Innovation: Generative AI can produce novel and innovative robot designs that may not have been conceived by human engineers. It explores a wide range of design possibilities, leading to more efficient and effective robots.
- Optimization: Generative AI can optimize robot designs for specific tasks or environments. It can consider various factors, such as materials, weight distribution, and energy efficiency, to create robots that perform better than traditional designs.
- Faster Prototyping: By rapidly generating and iterating on robot designs, generative AI reduces the time required for prototyping. This enables faster development and testing of new robotic systems, speeding up the overall research and development process.
- Cost Reduction: Generative AI can help identify cost-effective design solutions by minimizing the use of expensive materials and components. It can also reduce the need for extensive physical prototyping, saving both time and money.
- Adaptability: Robots designed using generative AI can be more adaptable to changing tasks and environments. They can quickly adapt their structure or behavior to meet new requirements, making them versatile in dynamic situations.
- Performance Enhancement: Generative AI can fine-tune robot designs for specific performance metrics, leading to robots that are more accurate, faster, and better suited to their intended tasks.
- Resource Efficiency: These AI-generated designs often lead to more resource-efficient robots. This is particularly important in applications where energy efficiency and sustainability are key considerations.
- Complex Structures: Generative AI can create intricate and complex robot structures that are difficult or impossible to design manually. This can result in robots with enhanced capabilities, such as improved mobility or dexterity.
- Customization: Robots can be designed with specific user requirements in mind. Whether it's for industrial automation, healthcare, or personal assistance, generative AI allows for tailored designs that cater to individual needs.
- Rapid Evolution: As generative AI algorithms continue to improve and learn, robot designs can evolve and adapt over time. This means that robots can continually improve their performance without the need for extensive manual redesign.
- Reduced Human Bias: Generative AI can reduce human bias in robot design. By relying on data and algorithms, it can generate designs that are more objective and free from preconceived notions.
- Scalability: AI-generated robot designs can be easily scaled for mass production, making it feasible to deploy robots in various industries and applications.
What kind of tool is the Solid Geometry Library Toolbox?
The SG-Lib is a toolbox for the Matlab math program from Mathworks. In some cases, other Matlab toolboxes are needed.
The goal is to automate the design process for the construction of robots. This concerns the design of rigid bodies, joints, kinematics, gears, but also shape optimization with Computer-Aided Optimization (CAO) or Topology Optimization (SKO) for both small motions (small displacement) and mechanism design (large displacement). Likewise, part of SG-Lib is dedicated to the simulation of multibody systems and the automatic generation of control codes for the µC of the Arduino family or the use of 2D or 3D area cameras. There is also a port for processing medical image data from CT/MRI.
Tim Lueth, Professor at Technical University of Munich, Germany
The Toolbox can be downloaded at Matlab Central (set of all SG-Lib versions) at GitHub (dedicates SG-Lib versions) for educational non-profit purpose. The Toolbox license always expires after about one year. Until then there is always a new version. The Toolbox will certainly be further developed until 2035.
The library grows with discussions and also by code of other researchers:
The pictures show some examples of mechanisms designed with the SG-Lib. The work is typically presented at the IEEE Conferences ICRA, IROS and ROBIO and many more: