Trajectory Optimization and Mission Planning for Quadrupedal Robots

背景和潜在影响研究只关注四足机器人（四足机器人），因为这些移动平台提供了非常吸引人的能力，可以穿越由人类设计的具有挑战性的地形和环境（楼梯和台阶）。我们的动态机器人系统组（DRS）在部署ANYmal用于具有挑战性的工业环境中的测绘，导航或检查任务方面具有专业知识。在COVID-19大流行之后，我调整了我的研究项目，以考虑参加实验室和办公空间的不确定性。因此，我专注于一个项目，我可以在家里工作，有很大的机会转移到机器人，而不需要进一步的开发。本研究包括使用因子图进行运动规划。该框架通常用于状态估计，因此其吸引力不仅在于为运动规划找到一种具有低计算时间的潜在新方法，而且还在于使用相同的工具解决两个关键问题。状态评估回顾过去，而计划展望未来。解决后一个问题意味着可以使用相同的工具来解决两个问题，从而提高这些算法的效率。接下来，我将回到最初的项目，在这个项目中，我想调查如何在全球任务规划框架中，我们可以更好地了解环境，以找到更好的任务计划。目前，DRS中现有管道处理的唯一信息仅为几何信息，例如通道的狭窄程度或地形的平坦程度。这对于现实世界的部署来说是不够的，因为地面类型不同（草地、鹅卵石、混凝土等），而且环境是由静态对象（如墙壁）和动态对象（门可以关闭或打开，盒子可以在某一天阻塞路径，但在另一天不会）组成的。需要考虑到这些信息，以增加将ANYmal等机器人部署到现实世界中的机会。本研究项目旨在利用机器人平台ANYmal提高自主操作能力。利用因子图开发轨迹优化管道。这一目标是针对2019冠状病毒病大流行后的封锁以及随后的实验室和办公空间封锁进行重新规划的结果。研究和开发。（Re-）使用现有解决方案（Gaitmesh结合Recast）规划全球任务。将语义信息（门、可移动物体）和其他物理信息（表面摩擦、地面类型）整合到规划算法中。框架参数优化研究方法的新颖性上述研究的新颖性在于：1。基于因子图的腿式机器人轨迹优化新方法，在四足机器人anymal上进行了展示和评价。新的任务能力，使机器人能够在全局任务的背景下规划和执行局部操作任务。EPSRC的战略一致性和研究领域本项目属于EPSRC工程研究领域。合作动态机器人系统组（DRS）参与了UKRI/EPSRC ORCA和RAIN机器人中心，以及H2020欧洲项目“THING”和“Memmo”。该项目将受益于英国和欧洲研究人员的广泛网络，而在此背景下的合作可能会有机增长。

Context and potential ImpactThe research focuses only on four-legged robots (quadrupeds) as these mobility platforms offer the highly appealing capability of traversing challenging terrain and environments designed by and for humans (stairs and steps). Our group, the Dynamic Robotic Systems group (DRS), has expertise in deploying the ANYmal for mapping, navigation or inspection missions in challenging industrial environments.Following the COVID-19 pandemic I adapted my research project to account for the uncertainty in attending lab and office space. As a result I focused on a project that I could work on mostly from home with a high chance of transferring to the robot without further need of development. This research consists of using factor graphs for motion planning. This framework is typically used in state estimation and thus the appeal lies in finding not only a potentially novel approach with low computation times for motion planning, but also in solving two crucial problems using the same tools. State estimation looks back in time while planning looks into the future. Solving the latter means that one could then move onto using the same tool for two problems and thus increasing the efficiency of these algorithms.Next I will return to the initial project in which I want to investigate how in global mission planning frameworks we can incorporate a better knowledge of the environment to find better mission plans. Currently the only information processed in the existing pipeline within DRS only accounts for geometric information such as how narrow a passage or flat a terrain is. This is not sufficient for real world deployments as the ground type differs (grass, pebble stones, concrete, ...) as well as the environment is made of static objects such as walls and dynamic objects (doors can be closed or open, a box can be blocking the path on one day but not on another). This information needs to be accounted for to increase the chances of deploying robots such as ANYmal into the real world.Aims and ObjectivesThe research project aims at improving the autonomous manipulation capabilities using the robotic platform ANYmal:1. Development of a trajectory optimization pipeline using factor graphs. This objective is a result of replanning for the lockdown following the COVID-19 pandemic and the following lockdown of the lab and office space.2. Research and development intoa. (Re-)Planning global missions using the existing solutions (Gaitmesh combined with Recast)b. Integration of semantic information (door, moveable objects) and other physical information (surface friction, ground type) into the planning algorithmc. Parameter optimization of the frameworkNovelty of the research methodologyThe novelty of the above mentioned research lies in1. New approach of trajectory optimization for legged robots using factor graphs, showed and evaluated on the quadruped ANYmal.2. New mission capabilities for the robot to plan, and execute loco-manipulation tasks in the context of global missions.EPSRC's strategy alignment and research areaThis project falls within the EPSRC Engineering research area.CollaborationsThe Dynamic Robot Systems group (DRS) is involved in the UKRI/EPSRC ORCA and RAIN Robotics Hubs, and the H2020 European Projects 'THING' and 'Memmo'. This project will benefit from access to this extensive network of UK and European researchers, while collaborations in this context are likely to organically grow.