Soft Robotic Cellbot for Extra-terrestrial Locomotion

该项目将解决两个研究挑战：1。驱动、形状改变和合并/分解：软体机器人必须能够改变其形状，以便在遥远星球上的不同地形上有效移动。多个软机器人“细胞”（小的软机器人单元）必须能够聚集在一起并融合，或者能够分解成更小的独立机器人。它们将利用这两种能力来增强它们的运动能力。2.智能与控制：细胞机器人必须感知它们的环境，并根据它们所处的地形智能地决定采用最佳形态，或者它们应该如何合并以形成新的3D形状，以获得在地形内操纵的最大形态优势。项目名称：在危险和不可接近的环境中，如外层空间，需要机器人在各种不平坦的地形上自主和有效地操纵。需要自主性，因为机器人和基站之间的通信通常存在延迟。一个软机器人群体具有形态适应能力的基础上的环境将提供一个有效的方法来解决这个问题。灵感来自于大自然的动物运动，在不可预测的地貌上移动。我们的目标是创建一个模块化的软机器人群，是由简单的球形元素，可以合并和协调其体积驱动，从而产生适合所遇到的环境运动。拥有大量的小型软机器人单元可确保可靠、经济高效和高容错的解决方案。机器人的柔软性允许机器人单元的形状容易改变，并通过允许其根据地形的粗糙度变形来增强其顺应性。在会话中，机器人可以很容易地放气和密集包装，以降低运输成本。到目前为止，该项目已经在Simscape中开发了细胞机器人的计算模型，其中运动周期和基本模型如图1所示。我们专注于优化机器人模型参数，了解摩擦系数对运动的影响，调整它们以实现最佳运动策略。当静摩擦处于过渡范围内时，在开始的几个循环期间，不同足部的足部位移值不同。图2显示了两只脚的相对相位图。对模型进行调整，以计算减去该开始时间后不同摩擦值下所有驱动周期内的平均足部位移。由此产生的结果将在稍后应用于更复杂的3D机器人模型。对所创建的模型的测试将包括将其从高处坠落，以测试在火星表面的迫降。这将有助于冲击测试和了解部署后的机器人运动。

This project will address two research challenges: 1. Actuation, shape change and coalescing/decomposition: The soft robot must be able to change its shape in order to move efficiently over different terrains on remote planets. Multiple soft robotic 'cells' (small soft robotic units) must be able to come together and fuse, or be able to decompose into smaller independent robots. They will exploit these two capabilities to enhance their locomotion capabilities. 2. Intelligence and control: Cellbots must sense their environments and intelligently decide the best morphology to adopt according to the terrain they are on, or how they should coalesce in order to form new 3D shapes, to obtain most morphological advantage in manoeuvring within the terrain. Project description: In hazardous and unapproachable environments, such as outer space, there is a need for robots to autonomously and efficiently manoeuvre over a variety of uneven topographies. Autonomy is required because there is commonly a delay in communication between robot and base station. A soft robotic swarm with the ability to morphologically adapt based on the surroundings would provide an effective way to tackle this problem. The inspiration is taken from nature based on the movement of animals, to move on unpredictable geomorphologies. The aim is to create a modular soft robot swarm that is composed of simple spherical elements that can coalesce and coordinate their volumetric actuation, thereby generating locomotion suitable to the encountered environment. Having a large number of small soft robotic units ensures a robust, cost-effective, and high fault tolerant solution. Softness in the robot allows for easy change of shape of the robotic units and enhances its compliance by allowing it to deform according to roughness of the terrain. In the session, the robot can easily be deflated and densely packed to reduce transportation costs. So far, the project has developed a computational model of a cellbot in Simscape where the locomotion cycle and fundamental model are shown in figure 1. We have focused on optimizing robot model parameters and understanding the effect of friction coefficients on locomotion, to tune them to achieve an optimal locomotion strategy. Foot displacement values were different for different feet during starting few cycles when static friction was in transition range. Figure 2 shows the relative phase plot for two feet. The model was adjusted to calculate average foot displacement over all actuation cycles for different frictional values after subtracting this starting time. Results from this will be later applied to a more complex 3D robot model. Tests on the model created will include dropping it from height to test for crash landing on Mar's surface. This will help in impact testing and understand robot locomotion after deployment.