Showing papers on "Autonomous system (mathematics) published in 1988"
••
01 Jun 1988TL;DR: The controller for an intelligent mobile autonomous system (IMAS), equipped with vision and low-level sensors to cope with unknown obstacles, is modeled as a hierarchy of decision-making for planning and control.
Abstract: The controller for an intelligent mobile autonomous system (IMAS), equipped with vision and low-level sensors to cope with unknown obstacles, is modeled as a hierarchy of decision-making for planning and control. One of the levels (pilot) deals with a distorted 'windshield' view of the world and provides the actuator controller with real-time decisions. This level of IMAS controller is treated as a linguistic controller with fuzzy variables that assume values from possible intervals. The decision-making process at this level of control are presented as a production system with a fuzzy database. The rules in the production system are derived from an analytical system model for minimum-time control. The choice of optimal motion execution commands is performed using fuzzy set operators. Also included is a temporal decision-making mechanism (reporter), which recognizes the persisting conflicts between successive levels of the hierarchy by observing the motion trajectory. >
97 citations
••
01 Jan 1988
6 citations
••
27 Oct 1988TL;DR: An interface between a partially autonomous system and external sources of knowledge is a feature which enables application of technology not yet fully autonomous in the development of the Telerobot Interactive Planning System.
Abstract: The telerobot interactive planning system (TIPS) has been developed to provide automated task planning and reasoning for satellite servicing in NASA's Jet Propulsion Laboratory telerobot testbed. The strategy taken in this development is that an interface between a partially autonomous system and external sources of knowledge is a feature which enables application of technology not yet fully autonomous. Interactive features, both between the operator and TIPS and among the reasoning engines within TIPS, result in a system which has greater robustness than the reasoning engines alone could provide.
4 citations
••
TL;DR: In this article the experience derived from designing locomotion control systems for both teleoperated and autonomous multi-legged articulated robots is described.
Abstract: AI researchers claim to understand some aspect of human intelligence when their model is able to “emulate” it. In the contexts of mobile robots, the ability to go from teleoperation to autonomy should accordingly be treated not simply as a trick for robotics hackers but as an important epistemological and methodological goal. In this article the experience derived from designing locomotion control systems for both teleoperated and autonomous multi-legged articulated robots is described.
2 citations