Impedance Control on Uncertain Objects

点击翻译按钮获取中文摘要

Robots have been able to serve the original promise to replace human counterparts in laborious, hazardous, and repetitive tasks mainly in the area of position control that includes tasks such as pick and place of components, arc welding, grinding known objects, and even in bipedal walking on fairly smooth and known grounds. However, robots still find it hard to carry out stable force control tasks on uncertain objects or walk on natural soft terrains (grass, sand, mud). Just like the difference between the way we use the left hand and the right hand can not be explained using their biomechanical basis alone, the answer to robotic survival in uncertain environments does not come from an attempt to build robots that resemble human bodies alone. From early 1980s, scientists have begun to believe that the secrets of stable interactions with natural compliant environments will come from an ability of the robot itself to be compliant. The original work of Neville Hogan on impedance control was based on this concept. Since then, a considerable body of literature can be found on how impedance control is applied in various force control applications such as rehabilitation, massaging, bipedal walking, exoskeletal robotics, and several other direct interactions with humans. However, still there is no answer to how impedance control should be adaptively managed to sustain stability when the coupled dynamics between the robot and the environment evolves metastable dynamics. The theory of Metastability states that an uncertain dynamics system can exhibit intermittent instability though it may stay stable most of the time. A human using a screw driver is one example, where the dynamic contact with the screw may stay stable most of the time, but exhibit intermittent slipping due to uncertainty in the friction between the screw and the surrounding medium. Even a human walker can fall down in rare situations due to the same phenomenon. However, an uncertain dynamic system can enhance stability if it can predict where it is likely to fail. A number of recent advances in metastable systems use the concept of mean first passage time (MFPT) as an indicator to assess the current control policy in an uncertain environment. MFPT is the expected time to the next failure situation given the current knowledge of the uncertain dynamics of the coupled dynamics of the robot and the environment.Therefore, this project aims at developing a unifying theory of impedance control for robots that are in dynamic contact with uncertain environments. The generic method that can start to perform stable hybrid position/force control on an uncertain environment with partially known dynamics and recursively build a robust internal model to perform stable position/force control on an environment that changed its stiffness, viscosity, and inertia. Then an algorithm will be developed to use a locally linearised model of the above coupled dynamic system to estimate the MFPT of the robot and the environment. This MFPT will then be used in a novel real-time algorithm to adapt a bank of candidate impedance parameter sets and adaptively choose the best parameter set to suit the environment in order to maximise the MFPT. Rigorous theoretical proofs of stability and experimental validation of methods will be given. The project will use a custom built experimental platform to evaluate and refine the fundamental theories and algorithms that will be developed in this project. The PI will closely collaborate with Shadow Robotics Company, a UK based SME who develops biomimetic robotic hands, and the robotics group led by Professor Darwin Caldwell at the Italian Institute of Technology, where the researchers strive to enable the humanoid robot i-Cub to interact with natural uncertain environments. Therefore, this project will benefit from a wealth of experiences the collaborators have already gathered on real robots interacting with natural environments.