摘要
由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-关于机器人的最新研究结果已经发表。根据NewsRx编辑在法国格勒诺布尔的新闻报道，研究表明，“许多移动机器人应用程序要求机器人围绕人类导航，人类可能会根据社交能力和意图来解释机器人的运动。”新闻记者从格勒诺布尔大学的研究中获得了一句话:“了解机器人运动的哪些方面与这种感知有关是至关重要的,这样我们就可以设计出合适的导航算法。目前在社会导航领域的工作倾向于追求一种单一的理想运动风格,这种风格是根据舒适性、自然性、本文首先提出了基于感知实验的Logistic回归模型，将人类的感知与线性速度分布图联系起来，证明了不同的轨迹特征对人类对机器人的社会感知有影响。我们将轨迹规划问题表述为约束优化的形式，使用新的约束条件，这些约束条件可以选择性地应用于轨迹的形状，从而产生期望的社会感知。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on robotics have been published. According to news reporting out of Grenoble, France, by NewsRx editors, research stated, "Many mobile robotics applications require robots to n avigate around humans who may interpret the robot's motion in terms of social at titudes and intentions." The news reporters obtained a quote from the research from University Grenoble A lpes: "It is essential to understand which aspects of the robot's motion are rel ated to such perceptions so that we may design appropriate navigation algorithms . Current works in social navigation tend to strive towards a single ideal style of motion defined with respect to concepts such as comfort, naturalness, or leg ibility. These algorithms cannot be configured to alter trajectory features to c ontrol the social interpretations made by humans. In this work, we firstly prese nt logistic regression models based on perception experiments linking human perc eptions to a corpus of linear velocity profiles, establishing that various traje ctory features impact human social perception of the robot. Secondly, we formula te a trajectory planning problem in the form of a constrained optimization, usin g novel constraints that can be selectively applied to shape the trajectory such that it generates the desired social perception."
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