New Lattice Framework Boosts Strength While Cutting Weight in Bionic Robot Legs

Researchers have unveiled a new lattice-based design method that makes bionic robot legs both lighter and stronger, achieving a 23 % weight reduction and a 97 % stiffness increase without sacrificing durability.

Robotic cyber dog on the plain background.

Study: Research on lower limb lightweight of bionic robot based on lattice structure unit. Image Credit: Phoenixproduction/Shutterstock.com

Published in Nature, the study outlines a systematic way to design and select optimal lattice structures, validated through experiments on a quadruped robot. The work is anticipated to help advance the field of lightweight robotics, where speed, precision, and efficiency are tightly linked to structural performance.

Why Lightweight Matters

In robotics and aerospace, weight reduction is not just about efficiency—it directly impacts speed, stability, and energy use. Lattice structures are attractive because they offer excellent strength-to-weight ratios, but until now, most approaches either mimicked biological forms or focused on isolated properties such as energy absorption or stiffness.

What was missing was a systematic method to evaluate and select lattice units capable of handling multiple, complex loads simultaneously.

This study fills that gap. The researchers created a library of 20 topology-optimized lattice designs, tested them under compression, bending, and torsion, and introduced a weighted evaluation method using the Analytic Hierarchy Process (AHP). This allowed them to identify the most effective structures for real-world multi-load conditions, moving lattice optimization from theory to practical application.

Designing and Testing Lattice Structures

Using Altair OptiStruct, the team generated 20 different lattice configurations, each optimized for specific loading conditions. The designs were then refined in SolidWorks to ensure manufacturability while maintaining mechanical performance. Key metrics—relative density and specific stiffness—were used to balance lightness with strength.

Finite element analysis revealed how stress and deformation played out across the different units. Unit 14 stood out, offering superior stiffness under compression, bending, and torsion. For complex scenarios involving multiple stresses, the weighted evaluation method combined with AHP provided a structured way to prioritize loading conditions and select the best unit for the job.

Experimental Validation

Mechanical testing confirmed the simulations. Using an Instron 3369 machine with custom fixtures, the team evaluated all 20 lattice units:

  • Compression: Unit 14 showed minimal displacement (0.336 mm) compared to Unit 7 (3.84 mm).
  • Bending: Unit 16 performed best (1.278 mm displacement), while Unit 3 was weakest (6.44 mm).
  • Torsion: Unit 13 offered the most resistance (0.428 mm) compared to Unit 3 (32.608 mm).

Load-displacement curves closely matched simulation predictions, and repeated testing confirmed the reliability of both the methodology and the lattice designs themselves.

The researchers then applied their method to the lower limb of a quadruped robot designed to support a 20-kilogram torso and withstand dynamic forces. Topology optimization identified regions of high stress and low importance, guiding material reduction. Using the AHP-weighted selection process, the team chose Unit 10 from their library to fill the robot’s leg structure.

The result was a leg nearly one-quarter lighter yet almost twice as stiff. Stress and displacement simulations confirmed that the new design preserved structural integrity, demonstrating its suitability for demanding robotic applications.

From Simulation to Reality

To see if their designs could hold up outside the computer, the team 3D-printed the optimized robot legs using SLA technology and put them through real-world testing on a custom platform.

Both the original and optimized legs were subjected to the same stresses, allowing the researchers to compare performance directly. The lattice-filled versions proved nearly a quarter lighter yet almost twice as stiff, a balance that can give robots greater agility without sacrificing durability.

During testing, the optimized legs deformed gradually and predictably under increasing loads, rather than collapsing suddenly, which is exactly the type of behavior engineers aim for in structures that need to be both strong and reliable. Just as importantly, the experimental data closely matched the results from finite element simulations, confirming that the design method translates consistently from computer models to physical hardware.

Conclusion

This study presents a practical framework for designing lightweight robotic structures, bringing together a comprehensive lattice library, systematic testing, and AHP-guided selection. The approach not only delivers substantial weight reduction and improved stiffness but also demonstrates clear potential for applications well beyond robotics.

The strong alignment between simulation results and real-world testing underscores the reliability of the method, offering engineers a dependable path toward creating systems that are both lighter and stronger.

Journal Reference

Shen, H., Wei, L., Zhang, T. et al. Research on lower limb lightweight of bionic robot based on lattice structure unit. Sci Rep 15, 29316 (2025). DOI:10.1038/s41598-025-14679-5. https://www.nature.com/articles/s41598-025-14679-5

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