… 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 …

… Task sequencing, ie, choosing an efficient sequence of tasks and the way the robot is moving
… The goal of the RKGA is to minimize the fitness/cost value vfitness of the robot drawing the …

… 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 …

… AV driving styles. We hypothesize that calibrating this cost function allows us to model
human driving styles in motion planning. The main contributions of this work are as follows: …

… 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 …

… of a weighted combination of three cost functions that have been experimentally observed
in humans: a hand jerk cost [44], an angular jerk cost [38], and a torque change cost [80]. The …