… The optimization cost function can be formulated in different ways. First, it can be defined or
… Extraction of person-specific motion style based on a task model and imitation by humanoid …

… robot without requiring complex reward functions. We also demonstrate that an effective style
reward can be learned from a few seconds of motion … motion priors results in a lower Cost …

… This is critical because of the high cost of running trials on a physical robot: not only must …
aspects of motion planning through continuous robot configuration space, AI-style planning …

… Unlike a strict hierarchical planning system, our planner integrates behavior and local motion
planning. … Posner, “Large-scale cost function learning for path planning using deep inverse …

… The cost function of this method is composed of the elastic band smoothness term, the …
lightweight and flexible and could transfer the style of realistic image to the simulated style, which …

… [33] developed a cost function considering the dual-arm robot configuration to determine
the most efficient path planning solutions for its human partner. Imajo et al. [34] addressed a …

… Using a dataset of participants performing a series of squatting tasks, we applied the proposed
method to recover the multiphase cost function underlying the continuous human motion …

… This article aims to: 1) make those ideas accessible to robotics and control … motion planning
[3], and motion optimization has leveraged Hessian to exploit the natural geometry of costs [5]…

… of the cost function to be optimized in typical approaches to generating human likeness in
robotic motions is a hotly debated topic. In order to not have to choose a cost function, Averta …

… to the real robot while maintaining the desired smooth and natural looking motion styles. Our
… The OP3 humanoid is a much more low-cost robot which results in a number of properties …