Knowledge acquisition and learning in unstructured robotic assembly environments
نویسندگان
چکیده
Mechanical assembly by robots has traditionally depended on simple sensing systems and the robot manufacturers programming language. However, this restricts the use of robots in complex manufacturing operations. An alternative to robot programming is the creation of self-adaptive robots based on the adaptive resonance theory (ART) artificial neural network (ANN). The research presented in this paper shows how robots can operate autonomously in unstructured environments. This is achieved by providing the robot with a primitive knowledge base (PKB) of the environment. This knowledge is gradually enhanced online based on the contact force information acquired during operations. The robot resembles a blindfold person performing the same task since no information is provided about the localisation of the fixed assembly component. The design of a novel neural network controller (NNC) based on the Fuzzy ARTMAP network and its implementation results on an industrial robot are presented, which validate the ap-
منابع مشابه
Distributed Architecture for Intelligent Robotic Assembly Part III: Design of the Invariant Object Recognition System
In previous chapter it has been described the overall architecture for multimodal learning in the robotic assembly domain (Lopez-Juarez & Rios Cabrera, 2006). The acquisition of assembly skills by robots is greatly supported by the effective use of contact force sensing and object recognition. In this chapter we will describe the robot’s ability to invariantly recognise assembly parts at differ...
متن کاملIntelligent learning and control of autonomous robotic agents operating in unstructured environments
The control of autonomous intelligent robotic agent operating in unstructured changing environments includes many objective difficulties. One major difficulty concerns the characteristics of the environment that the agent should operate in. In unstructured and changing environments the inconsistency of the terrain, the irregularity of the product and the open nature of the working environment r...
متن کاملOn the design of intelligent robotic agents for assembly
Robotic agents can greatly be benefited from the integration of perceptual learning in order to monitor and adapt to changing environments. To be effective in complex unstructured environments, robots have to perceive the environment and adapt accordingly. In this paper it is discussed a biology inspired approach based on the adaptive resonance theory (ART) and implemented on an KUKA KR15 indus...
متن کاملLearning and adaptation of an intelligent mobile robot navigator operating in unstructured environment based on a novel online Fuzzy-Genetic system
In this paper we present our novel Fuzzy–Genetic techniques for the online learning and adaptation of an intelligent robotic navigator system. Such a system could be used by autonomous mobile vehicles navigating in unstructured and changing environments. In this work we focus on the online learning of the obstacle avoidance behaviour, which is an example of a behaviour that receives delayed rei...
متن کاملA Model-Based Goal-Directed Bayesian Framework for Imitation Learning in Humans and Machines
Imitation offers a powerful mechanism for knowledge acquisition, particularly for intelligent agents (like infants) that lack the ability to transfer knowledge using language. Several algorithms and models have recently been proposed for imitation learning in humans and robots. However, few proposals offer a framework for imitation learning in noisy stochastic environments where the imitator mu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Inf. Sci.
دوره 145 شماره
صفحات -
تاریخ انتشار 2002