EPIROME - A novel framework to investigate high-level episodic robot memory

Jockel, Sascha; Westhoff, Daniel; Zhang, Jianwei

doi:10.1109/robio.2007.4522313

Cited by 16 publications

(12 citation statements)

References 10 publications

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“…In this work SDM learning is constrained to the 6-degree-offreedom MHI PA10-6C robot arm trajectory for manipulation tasks. For further specifications of the used robot system, see [14], [15]. Manipulation is based on a sequence of 3-D coordinates and roll, pitch, and yaw angles of the manipulation tool.…”

Section: Experimental Platformmentioning

confidence: 99%

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Sparse distributed memory for experience-based robot manipulation

Jockel¹,

Lindner²,

Zhang³

2009

2008 IEEE International Conference on Robotics and Biomimetics

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Abstract-Sparse distributed memory (SDM) is a mathematical technique based on the properties of high-dimensional space for storing and retrieving large binary patterns. This model has been proposed for cerebellar functions, and has been used in simple visual and linguistic applications to date. This paper presents an SDM for robotic applications, especially for storing and recognising mobile manipulation actions of a 6-DOF robot arm. Sequences of events are stored as subjective experiences and are later used to guide robot arm behaviour based on its memory content. Several simple manipulation tasks, such as lift and place a wastebin from and on the floor, push an object aside on a tabletop, and draw shapes in the air are analysed under different operation modes. The robot system shows good reproduction abilities of task-dependent arm trajectories based on sparse distributed memory. Moreover, the content-addressable, associative memory even predicts the residual arm trajectory of a task if the arm is placed somewhere close to a learnt trajectory.

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Section: Experimental Platformmentioning

confidence: 99%

“…During subsequent autonomous executions, the robot is supposed to recognise its current joint constellation to navigate the robot arm driven by its memory of past experiences. This paper is a part of an ongoing investigation into the feasibility of using SDM for robot control and memory-based action prediction [14], [15].…”

Section: Introductionmentioning

confidence: 99%

Sparse distributed memory for experience-based robot manipulation

Jockel¹,

Lindner²,

Zhang³

2009

2008 IEEE International Conference on Robotics and Biomimetics

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“…It can provide one-shot learning capabilities to robot. 13 The episodic memories retained a sequence of experienced observation, behaviour and reward. 8 Simulation research of navigation task was processed through the observation of distance information.…”

Section: Introductionmentioning

confidence: 99%

A biological-inspired episodic cognitive map building framework for mobile robot navigation

Liu

Cong

Zou

et al. 2017

International Journal of Advanced Robotic Systems

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This article proposes a self-learning method of robotic experience for building episodic cognitive map using biologically inspired episodic memory. The episodic cognitive map is used for robot navigation under uncertainty. Two main challenges which include high computational complexity and perceptual aliasing are addressed. The episodic memory-driving Markov decision process is proposed to simulate the organization of episodic memory by introducing neuron activation and stimulation mechanism. Episodic memory self-learning model and algorithm are presented for building the episodic cognitive map based on episodic memory-driving Markov decision process. Uncertain information is considered to improve mapping performance. The presented method can realize robotic memory real-time storage, incremental accumulation, integration and updating. Based on the episodic cognitive map, the predicted episodic trajectory can simply be computed by activation spreading of state neurons. The experimental results for a mobile robot indicate that the method can efficiently performs learning, localization, mapping and navigation in real-life office environments.

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“…Among the various approaches in the literature, Stachowicz and Kruijff provide a thorough explanation of both design requirements and formal concepts needed to characterize EM and its storage structure [10]. They also provide a brief review about EM in the ISAC framework [5], the SOAR architecture [4], and EPIROME [7], just to name but a few. However, the focus of their work is on the notion of event, its properties, and its use in such processes as event recognition, event nesting, and event types of complexity.…”

Section: Introductionmentioning

confidence: 99%

An integrated epigenetic robot architecture via context-influenced long-term memory

Pratama

Mastrogiovanni

Chong

2014

4th International Conference on Development and Learning and on Epigenetic Robotics

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In this paper, we present a conceptual design for a context-influenced Long-Term Memory architecture. The notion of context is used as a means to organize the information flow between the Working Memory and Long-Term Memory components. In particular, we discuss the major influence of the notion of context within the Episodic Memory on the Semantic and Procedural Memory, respectively. In other words, we address how the occurrence of specific events in time impacts on the meaning of those events and the subsequent use of objects through robot actions. The general architecture design and its implementation in a simulated scenario are described. Such issues as memory items representation, individual structures of Long-Term Memory components, as well as memory-based recognition and item retrieval processes, are discussed in detail.

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EPIROME - A novel framework to investigate high-level episodic robot memory

Cited by 16 publications

References 10 publications

Sparse distributed memory for experience-based robot manipulation

Sparse distributed memory for experience-based robot manipulation

A biological-inspired episodic cognitive map building framework for mobile robot navigation

An integrated epigenetic robot architecture via context-influenced long-term memory

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