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Modeling and control techniques for a class of mobile-robot error recovery problems.

机译:用于一类移动机器人错误恢复问题的建模和控制技术。

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A robot's locomotion mode fails when its environmental contacts fail, a situation called a locomotion error. For example, a legged robot cannot move when its leg becomes trapped in a crevice, and a wheeled robot is handicapped when its wheels skid. How can a robot recover when its standard locomotion mode fails? One way is to utilize any remaining freedoms to move the robot to a situation where the robot's standard locomotion mode is again feasible. However, planning and control for such unconventional motion is difficult, since the relationship between the robot's controls and its motion in a locomotion error is unclear. This complexity when combined with the uncertainty in environmental interaction (perceived as an "element of luck") in a locomotion error appears as a lack of structure, inducing operators to sometimes use random escape maneuvers. This thesis proposes finding recovery strategies by exploiting the structure inherent to the robot's constrained mobility and environmental interaction in the locomotion error. A robot equipped with multiple locomotion modes can choose between them depending on the circumstance, ultimately contributing to robust mobility.; While robotic locomotion fails in many ways depending on the robot's design and the environmental interaction, this thesis finds novel recovery modes involving a combination of direct actuation and dynamically coupled actuation for two specific locomotion errors: first, a high-centered legged robot, where the robot's legs dangle in air; and second, a car trapped in a slippery pit. In the high-centered robot problem, we present a novel locomotion mode called "legless locomotion", that allows the robot to locomote by rocking its body back and forth using leg swing without feedback about the robot's body motions. We use experiments and computer simulation to identify legless locomotion's properties and use simple models to derive an approximate control technique. In the car-in-ditch problem, we use computer simulation to find a control strategy involving wheel torques and an active-suspension that allows the car to roll out of the pit, while minimizing work done and perturbations to the car body. Finally, we present a classification structure for locomotion errors based on environmental influence.
机译:当机器人的环境接触失败时,其运动模式就会失败,这种情况称为运动错误。例如,当腿式机器人的腿陷入缝隙中时,腿式机器人将无法移动,而当轮子打滑时,轮式机器人将无法使用。当机器人的标准运动模式失败时,如何恢复?一种方法是利用任何剩余的自由度将机器人移动到机器人的标准移动模式再次可行的情况。但是,由于机器人控制与运动误差中的运动之间的关系尚不清楚,因此难以计划和控制此类非常规运动。这种复杂性与运动错误中的环境相互作用的不确定性(被视为“运气要素”)相结合,表现为缺乏结构,从而导致操作人员有时会使用随机逃生操作。本文提出了通过利用机器人在运动误差中受约束的移动性和环境相互作用固有的结构来寻找恢复策略。具有多种运动模式的机器人可以根据情况在它们之间进行选择,最终有助于实现强大的移动性。尽管机器人运动会因机器人的设计和环境相互作用而在许多方面失败,但本文发现了针对两种特定运动错误的新颖恢复模式,其中涉及直接致动和动态耦合致动的组合:首先是高中心腿式机器人,其中机器人的腿悬在空中;第二,一辆汽车被困在一个湿滑的坑中。在高中心机器人问题中,我们提出了一种称为“无腿运动”的新型运动模式,该模式允许机器人通过使用腿部摆动来回摆动身体而进行运动,而无需反馈有关机器人身体运动的信息。我们使用实验和计算机仿真来识别无腿运动的特性,并使用简单的模型来推导近似控制技术。在沟内问题中,我们使用计算机仿真来找到一种控制策略,该策略涉及车轮扭矩和主动悬架,该悬架可以使汽车滑出维修区,同时最大程度地减少对车身的影响和扰动。最后,我们提出了基于环境影响的运动错误的分类结构。

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