In this paper, we propose a novel vision-based control algorithm for regulating the whole body shape of extensible multisection soft continuum manipulators. Contrary to existing vision-based control algorithms in the literature that regulate the robot's end effector pose, our proposed control algorithm regulates the robot's whole body configuration, enabling us to leverage its kinematic redundancy. Additionally, our model-based 2.5D shape visual servoing provides globally stable asymptotic convergence in the robot's 3D workspace compared to the closest works in the literature that report local minima. Unlike existing visual servoing algorithms in the literature, our approach does not require information from proprioceptive sensors, making it suitable for continuum manipulators without such capabilities. Instead, robot state is estimated from images acquired by an external camera that observes the robot's whole body shape and is also utilized to close the shape control loop. Traditionally, visual servoing schemes require an image of the robot at its reference pose to generate the reference features. In this work, we utilize an inverse kinematics solver to generate reference features for the desired robot configuration and do not require images of the robot at the reference. Experiments are performed on a multisection continuum manipulator demonstrating the controller's capability to regulate the robot's whole body shape while precisely positioning the robot's end effector. Results validate our controller's ability to regulate the shape of continuum robots while demonstrating a smooth transient response and a steady-state error within 1 mm. Proof-of-concept object manipulation experiments including stacking, pouring, and pulling tasks are performed to demonstrate our controller's applicability.

翻译：本文提出了一种新颖的基于视觉的控制算法，用于调控可扩展多节段软体连续型机械臂的整体形状。与现有文献中仅调控机器人末端执行器位姿的视觉控制算法不同，我们提出的控制算法调控机器人的整体构型，从而能够利用其运动学冗余特性。此外，与文献中报告局部极小值的最接近研究相比，我们基于模型的2.5维形状视觉伺服在机器人的三维工作空间中提供了全局稳定的渐近收敛性。与现有文献中的视觉伺服算法不同，我们的方法不需要来自本体感受传感器的信息，因此适用于不具备此类功能的连续型机械臂。相反，机器人状态通过观察机器人整体形状的外部摄像头获取的图像进行估计，并用于闭合形状控制回路。传统上，视觉伺服方案需要机器人在参考位姿下的图像来生成参考特征。在本工作中，我们利用逆运动学求解器为期望的机器人构型生成参考特征，而不需要机器人在参考状态下的图像。我们在多节段连续型机械臂上进行了实验，证明了控制器在精确定位机器人末端执行器的同时调控机器人整体形状的能力。结果验证了我们的控制器在调控连续型机器人形状方面的能力，同时展示了平滑的瞬态响应和小于1毫米的稳态误差。我们还进行了概念验证性物体操作实验，包括堆叠、倾倒和拉动任务，以证明我们控制器的适用性。