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The probabilistic roadmap approach is one of the leading motion planning techniques.
Proximity operations around small bodies are characterized by complex dynamics and constraints that can be easily and autonomously handled by motion planning techniques.
Following the Rabi oscillations used by physicists to control stimulated transition, we associate to this system an averaged control system where the number of controls is increased and where flatness-based motion planning techniques can be used.
Furthermore, motion planning techniques can be adapted to model molecular motions [ 10- 12], providing an attractive alternative to the mentioned approaches due to their efficiency.
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We present a novel motion planning technique for robot formations in such kinds of environments, which computes the most likely global path in terms of a defined minimum expected length (EL).
The proposed algorithms are tested to be incorporated as part of the design of a new motion control system to integrate reactive obstacle avoidance with local path planning techniques to provide safe real-time guidance capabilities.
This was overcome by using participatory planning techniques [ 15].
This paper presents a method to determine if a usable wheelchair accessible route in a facility exists using motion-planning techniques.
This paper presents example cases from architectural practice to illustrate the use of robot motion-planning techniques for wheelchair accessibility analysis.
We then described a human subject experiment aimed at studying human response to this motion-planning technique and quantifying its potential benefits through quantitative team fluency metrics and subjective evaluation of satisfaction, safety, and comfort.
In this paper, we presented an adaptive motion-planning technique that we call human-aware motion planning, which uses the prediction of human actions and workspace occupancy to actively avoid potential motion conflicts that could arise in close-proximity human robot interaction.
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