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This paper describes a cognitive map building system based on episodic memory for mobile robots. Inspired by the biological findings on the mammalian hippocampus, we proposed a novel method of episodic memory modeling which including a sequence of experienced observations, neutral states, behaviors and pose perceptions. The presented method can autonomously and incrementally learn the environmental...
The robot path planning for forming complex parts is one of the key techniques in coaxial laser cladding powder. In this paper, a method of automatic robot path generation from CAD (computer aided design) is proposed. The size information and topological information of the CAD model are extracted. The redundant vertexes are removed. The new vertexes are ordered and traversed by binary tree algorithm...
This paper proposes a framework called Episodic memory-driving Markov decision processes (EM-MDPs) for incremental self-learning of robotic experience and cognitive behavior control under uncertainty. The framework simulates the organization process of episodic memory by introducing the neuron stimulation mechanism. Firstly, episode model is built, and the activation and stimulation mechanism of state...
This paper proposes a vision-based behavior selection system using biologically-inspired visual attention selection mechanisms, i.e., Bottom-Up attention and Top-Down attention. We adopt purely Bottom-Up attention selection to identify conspicuous regions for obtaining the salient landmarks, while propose an object-based Top-Down attention method using low dimensional task-relevant feature for searching...
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