Sådhanå (2018) 43:28 Ó Indian Academy of Sciences https://doi.org/10.1007/s12046-018-0788-z Sadhana(0123456789().,-volV)FT3](0123456789().,-volV) An engineering-design oriented exploration of human excellence in throwing SUSHEEL DHARMADHIKARI1,* and ANINDYA CHATTERJEE2 1 Structural Dynamics Team, Eaton Technologies, EON IT Park, Pune 411014, India 2 Department of Mechanical Engineering, Indian Institute of Technology, Kanpur 208016, India e-mail:
[email protected];
[email protected] MS received 3 November 2016; revised 12 March 2017; accepted 19 July 2017; published online 10 March 2018 Abstract. Humans are fast throwers, and their bodies differ correspondingly from those of other hominids. One might ask why humans evolved to throw fast while others did not; whether the design of a fast thrower is unique or special and whether indeed humans remain fast within broader comparison sets of non-hominid throwers. As a non-hominid comparison set, we consider a random population of five-link robots with simplified joint angle and torque constraints. We generate 20,000 such robot models and sequentially optimize their throwing motion. Since good initial guesses are needed for each optimization, the robots are first arranged in distance-minimizing sequences in design parameter space. Each robot’s optimal throw then serves as an initial guess for the next one in sequence. Multiple traversals of these sequences, and random perturbations, are used to avoid local optima. Subsequently, regression models are used to predict throwing performance as a function of robot design parameters. From these regression models, the dominant heuristic predictor of fast throwing is found to be a long and light last link.