The biomimetic approach in robotics is promising: nature has found many good solutions through millions of years of evolution. However, creating a design that enables fast and energy-efficient locomotion remains a major challenge. This paper focuses on the development of a full leg mechanism for a fast and energy-efficient 4-legged robot inspired by a cheetah morphology. In particular, we analyze how the allocation of flexible elements and their stiffness affects the cost of transport and peak power characteristics for vertical jumps and a galloping motion. The study includes the femur and full leg mechanism's locomotory behavior simulation, capturing its interaction with the ground.

Practical identifiability of Systems Biology models has received a lot of attention in recent scientific research. It addresses the crucial question for models’ predictability: how accurately can the models’ parameters be recovered from available experimental data. The methods based on profile likelihood are among the most reliable methods of practical identification. However, these methods are often computationally demanding or lead to inaccurate estimations of parameters’ confidence intervals. Development of methods, which can accurately produce parameters’ confidence intervals in reasonable computational time, is of utmost importance for Systems Biology and QSP modeling. We propose an algorithm Confidence Intervals by Constraint Optimization (CICO) based on profile likelihood, designed to speed-up confidence intervals estimation and reduce computational cost. The numerical implementation of the algorithm includes settings to control the accuracy of confidence intervals estimates. The algorithm was tested on a number of Systems Biology models, including Taxol treatment model and STAT5 Dimerization model, discussed in the current article. The CICO algorithm is implemented in a software package freely available in Julia (https://github.com/insysbio/LikelihoodProfiler.jl) and Python (https://github.com/insysbio/LikelihoodProfiler.py).

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