Journal Article10.1142/6164
Evolutionary Robotics: From Algorithms to Implementations
Lingfeng Wang,Kay Chen Tan,Chee-Meng Chew +2 more
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TL;DR: Evolutionary robotics focuses on developing algorithms and implementations for autonomous robot navigation, sensor fusion, learning, and walking control. It includes task-oriented developmental learning for humanoids, gait optimization, and swing time generation.
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Abstract: Artificial Evolution Based Autonomous Robot Navigation Evolvable Hardware in Evolutionary Robotics FPGA-Based Autonomous Robot Navigation via Intrinsic Evolution Intelligent Sensor Fusion and Learning for Autonomous Robot Navigation Task-Oriented Developmental Learning for Humanoid Robots Bipedal Walking Through Reinforcement Learning Swing Time Generation for Bipedal Walking Control Using GA Tuned Fuzzy Logic Controller Bipedal Walking: Stance Ankle Behavior Optimization Using Genetic Algorithm.
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Citations
In Vivo Veritas: Towards the Evolution of Things
Agoston E. Eiben
- 13 Sep 2014
TL;DR: It will be possible to create populations of animate physical objects that undergo evolution in real space and real time and this will ignite the development of a new field that combines Evolutionary Computing, Robotics, Artificial Life, and Embodied AI with a great potential for engineering as well as scientific research.
•Dissertation
An energy-aware architecture : a practical implementation for autonomous underwater vehicles
Valerio De Carolis
- 01 Feb 2017
TL;DR: A novel energy-aware architecture for autonomous underwater vehicles (AUVs) is presented, capable of detecting and mitigating failures in the propulsion subsystem, one of the most common sources of mission-time problems and allowing the optimisation of on-board resource usage.
3
An empirical evaluation of evolutionary controller design methods for collective gathering task
Jae Jang
- 01 Jan 2015
TL;DR: In this article, the performance of evolutionary controller design methods for developing a collective behavior for a team of robots was evaluated in a collective gathering task, where robots were asked to cooperate in finding and retrieving items of interest.
1
Speech Driven Backchannel Generation using Deep Q-Network for Enhancing Engagement in Human-Robot Interaction
Nusrah Hussain,Engin Erzin,T. Metin Sezgin,Yücel Yemez +3 more
- 05 Aug 2019
TL;DR: Deep Q-network (DQN) is introduced in a batch reinforcement learning framework, where an optimal policy is learned from a batch data collected using a more controlled policy.
Energy-aware fault-mitigation architecture for underwater vehicles
TL;DR: An energy-aware architecture that by observing the use of the on-board resources is capable of detecting faults and monitors the performance of the thruster subsystem in modern AUVs is introduced.
References
•Book
Soft Computing and Tools of Intelligent Systems Design: Theory and Applications
Fakhri Karray,Clarence De Silva +1 more
- 01 Jun 2004
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