...John N. Nganga; Patrick M. Wensing This letter presents approaches that reduce the computational demand of including second-order dynamics sensitivity information into optimization algorithms for robots in contact with the environment. A full second-order differential dynamic programming (DDP...

... optimization problem is required for which efficient algorithms exist [ 5 – 8 ]. Office of Naval Research 10.13039/100000006 N00014-22-1-2131 computational methods constrained control nonlinear control optimization algorithms 19 08 2022 16 12 2022 16 12 2022 24...

... such as evolutionary algorithms [ 9 ], genetic algorithms [ 10 ], and metaheuristic optimization algorithms [ 11 , 12 ]. These optimization methods can tackle nonlinear coupled systems and produce the desired performance. Among all of these algorithms, the relatively new metaheuristic optimization routine called...

... ], which saves the computation effort associated with solving the SDEs in the time domain. This study solves the SDEs in the time domain, such that the solution can be incorporated into optimization algorithms to calibrate the model against time-series data. This section outlines the concept of SDE...

... constrained control control applications H infinity control linear matrix inequality (LMIs) optimization algorithms robust control uncertain systems vibration control vibrations The demand for cloud storage is ever increasing today, requiring more efficient storage options. Hard disk drives...

... analysis understory vegetation density automotive systems computational methods identification machine learning modeling optimization algorithms unmanned vehicles Scene understanding and traversability analysis are challenging tasks for autonomous driving applications. For off-road...

... and first-responder robots have been developed in various forms. dynamics and control optimization algorithms vibration control 25 10 2019 09 02 2020 16 02 2020 18 03 2020 Email: jun.ueda@me.gatech.edu Email: yong.cho@ce.gatech.edu Email: cshan@hanyang.ac.kr...

..., a standard nonlinear moving horizon formulation leads to non-convex optimization problems, and numerical optimization algorithms can be trapped in undesirable local minima, leading to incorrect solutions. To address the challenge of non-convex cost functions, we propose an estimator with a two-level...