Autonomous physics-based object manipulation

物体操作规划是机器人技术中的一个重要问题。想象一下，一个自主的家庭助手机器人伸手到一个杂乱的冰箱架子上：机器人需要与多个物体接触并将它们推开。机器人的动作必须仔细规划，以避免将物体从架子上推下来，导致它们掉下来并破裂。现有的算法通过搜索可能的动作序列来解决这个规划问题。每个动作应用于一个离散的时间步长，规划器选择预测的序列，以达到目标对象，而不破坏场景中的其他对象。在时间步长期间，每个动作的效果使用物理模拟来计算，物理模拟可以是完整的动态模拟，也可以是简化的准静态模型。然而，现有算法的一个主要问题是速度：可能的行动序列的数量随着规划范围呈指数增长，导致无法接受的长规划时间。减少规划时间的新方法可以对这一领域产生重大影响，使机器人能够执行目前超出其能力的操作任务。在这个项目中，我们将开发新的基于优化的方法来自主地在杂乱中进行基于物理的对象操作。

Planning of object manipulation is an important problem in robotics. Imagine an autonomous home-helper robot reaching into a cluttered fridge shelf: the robot will need to make contact with multiple objects and push them out the way. The robot's actions must be carefully planned to avoid pushing objects off the shelf, causing them to fall down and break. Existing algorithms solve this planning problem by searching over possible sequences of actions. Each action is applied for a discrete time step, and the planner chooses the sequence which is predicted to reach the goal object without damaging other objects in the scene. The effect of each action during a time step is computed using a physics simulation, which can either be a complete dynamics simulation or a simplified quasi-static model. However, a major problem with existing algorithms is speed: The number of possible action sequences increases exponentially with the planning horizon, leading to unacceptably long planning times. New methods that reduce planning time can have a major impact in this area, enabling robots to perform manipulation tasks that currently exceed their capabilities. In this project we will develop new optimisation based approaches to autonomous physics-based object manipulation in clutter.