Recent advancements in constrained kinematic control make it an attractive strategy for controlling robots with arbitrary geometry in challenging tasks. Most current works assume that the robot kinematic model is precise enough for the task at hand. However, with increasing demands and safety requirements in robotic applications, there is a need for a controller that compensates online for kinematic inaccuracies. We propose an adaptive constrained kinematic control strategy based on quadratic programming, which uses partial or complete task-space measurements to compensate online for calibration errors. Our method is validated in experiments and simulations that show increased accuracy and safety compared to a state-of-the-art kinematic control strategy.
翻译：最近限制运动控制的进展使得它成为一项具有挑战性任务任意几何特征的机器人控制的有吸引力的战略。大多数目前的工程假设机器人运动模式足以精确地完成手头的任务。然而,随着机器人应用中日益增长的需求和安全要求,需要有一个控制器来补偿网上的运动不准确性。我们提议一个适应性有限运动控制战略,其依据是二次程序,它使用部分或完整的任务空间测量来补偿网上校准错误。我们的方法在实验和模拟中得到了验证,这些实验和模拟表明,与最先进的运动控制战略相比,准确性和安全性都有所提高。
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