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Problems of temporal granularity in robot control: Levels of adaptation and a necessity of self-confidence

机译:机器人控制中的时间粒度问题:适应程度和自信心的必要性

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The granularity of “action” within a system is highly depending on the internal representation for the task, or intention of what to do if it is a biological system. In the same time, there are several levels of adaptation when the system tries to complete a mission. The problem of choosing the right level of action representation is essential for robot controls as well as in learning paradigms. Both tend to use low-granularity and transfer the processed information to upper levels constructively. However the system never guarantees the completion time of the mission if the system is composed of stiff functional blocks with a specific temporal granularity at the bottom level. However, we biological system have an ability to manage the global time for scheduling and reorganization of tasks to finish by the deadline. Brain-inspired robotics allows us to investigate a distributed parallel information system, the brain, with the ability of time management as a real time control system of the physical body through flexible planning of necessary actions by interacting with the real environment. It is an extension of subsumption approaches that fixed a set of behaviors as the basic unit of action in the viewpoint of temporal property. By focusing on the temporal granularity as a consequence of coordination among multiple levels, a self-confident robot control may arise from a coupling between top-down or purpose-oriented decomposition of the purpose to primitive functions with flexible time windows and bottom-up of sensori-motor reactions in dynamic environments.
机译:系统内“动作”的粒度高度取决于任务的内部表示形式,或者取决于它是生物系统时要做什么的意图。同时,当系统尝试完成任务时,会有多个适应级别。选择正确的动作表示级别的问题对于机器人控制以及学习范例至关重要。两者都倾向于使用低粒度,并且将处理后的信息建设性地传递到较高级别。但是,如果系统由底层具有特定时间粒度的刚性功能块组成,则系统永远无法保证任务的完成时间。但是,我们的生物系统有能力管理全球时间,以安排任务的安排和重组,以在截止日期之前完成。受大脑启发的机器人技术使我们能够研究分布式并行信息系统,即大脑,它通过与实际环境进行交互来灵活地计划必要的动作,从而将时间管理作为身体的实时控制系统。从时间属性的角度来看,这是包容方法的扩展,它固定了一组行为,将其作为基本的动作单位。通过关注由于多个级别之间的协调而导致的时间粒度,自信的机器人控制可能源自对目标的自上而下或面向目标的分解到具有灵活时间窗和自下而上的原始功能之间的耦合。动态环境中的感觉运动反应。

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