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Model-Based Estimation of the Gravity-Loaded Shape and Scene Depth for a Slim 3-Actuator Continuum Robot with Monocular Visual Feedback

机译:具有单目视觉反馈的超薄三执行器连续体机器人重力加载形状和景深的基于模型的估计

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Fruitful developments on continuum robots have been witnessed in recent years due to their movements and manipulation capabilities in confined spaces. Due to the nature that a continuum robot has an infinite number of DoFs (Degrees of Freedom), majority of the existing systems deployed abundant actuators such that the robot can be controlled in separately modeled and actuated segments with constant or variable curvature. As the shape of a continuum robot is always jointly determined by its actuation and the interactions from the environment, it is hence worth exploring the opposite approach that how a task can be accomplished with a minimal number of actuators. This paper presents the first step of such an investigation where a slim 3-actuator continuum robot is actuated to reach different spatial locations under gravity. As the gravity greatly affects the robot's shape, a monocular camera, together with two UKFs (Unscented Kalman Filters), was used to concurrently estimate the robot's shape and the feature depth. Then the estimated shape can be used in updating the kinematics model of the robot to achieve motion control. Experiments were conducted to validate the effectiveness of the proposed shape estimation, which promises the motion control implementation in the near future work.
机译:近年来,由于连续机器人在受限空间中的移动和操纵能力,其发展取得了丰硕的成果。由于连续性机器人具有无限数量的DoF(自由度)的性质,大多数现有系统都部署了丰富的执行器,因此可以在具有恒定或可变曲率的单独建模和执行段中对机器人进行控制。由于连续性机器人的形状始终由其致动和来自环境的相互作用共同确定,因此值得探索相反的方法,即如何用最少数量的致动器来完成一项任务。本文介绍了这种研究的第一步,其中一个细长的3致动器连续体机器人被驱动以在重力作用下到达不同的空间位置。由于重力极大地影响了机器人的形状,因此使用了单眼相机以及两个UKF(无味卡尔曼滤镜)来同时估计机器人的形状和特征深度。然后,可以将估计的形状用于更新机器人的运动学模型以实现运动控制。进行了实验以验证所提出的形状估计的有效性,这有望在不久的将来实现运动控制。

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