Publications
Below is a list of all relevant publications authored by Robotics Forum members.
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Conference paperAhmadzadeh SR, Kormushev P, Caldwell DG, 2013,
Autonomous robotic valve turning: A hierarchical learning approach
, 2013 IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 4629-4634, ISSN: 1050-4729Autonomous valve turning is an extremely challenging task for an Autonomous Underwater Vehicle (AUV). To resolve this challenge, this paper proposes a set of different computational techniques integrated in a three-layer hierarchical scheme. Each layer realizes specific subtasks to improve the persistent autonomy of the system. In the first layer, the robot acquires the motor skills of approaching and grasping the valve by kinesthetic teaching. A Reactive Fuzzy Decision Maker (RFDM) is devised in the second layer which reacts to the relative movement between the valve and the AUV, and alters the robot's movement accordingly. Apprenticeship learning method, implemented in the third layer, performs tuning of the RFDM based on expert knowledge. Although the long-term goal is to perform the valve turning task on a real AUV, as a first step the proposed approach is tested in a laboratory environment. © 2013 IEEE.
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Conference paperKarras GC, Bechlioulis CP, Leonetti M, et al., 2013,
On-Line Identification of Autonomous Underwater Vehicles through Global Derivative-Free Optimization
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Conference paperKormushev P, Caldwell DG, 2013,
Improving the Energy Efficiency of Autonomous Underwater Vehicles by Learning to Model Disturbances
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Conference paperAhmadzadeh SR, Kormushev P, Caldwell DG, 2013,
Visuospatial Skill Learning for Object Reconfiguration Tasks
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Conference paperAhmadzadeh SR, Kormushev P, Caldwell DG, 2013,
Interactive Robot Learning of Visuospatial Skills
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Conference paperAhmadzadeh SR, Leonetti M, Kormushev P, 2013,
Online Direct Policy Search for Thruster Failure Recovery in Autonomous Underwater Vehicles
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Conference paperKormushev P, Caldwell DG, 2013,
Towards Improved AUV Control Through Learning of Periodic Signals
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Conference paperKormushev P, Caldwell DG, 2013,
Comparative Evaluation of Reinforcement Learning with Scalar Rewards and Linear Regression with Multidimensional Feedback
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Conference paperJamali N, Kormushev P, Caldwell DG, 2013,
Contact State Estimation using Machine Learning
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Conference paperLeonetti M, Ahmadzadeh SR, Kormushev P, 2013,
On-line Learning to Recover from Thruster Failures on Autonomous Underwater Vehicles
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Conference paperKormushev P, Caldwell DG, 2013,
Reinforcement Learning with Heterogeneous Policy Representations
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Conference paperKryczka P, Hashimoto K, Takanishi A, et al., 2013,
Walking Despite the Passive Compliance: Techniques for Using Conventional Pattern Generators to Control Instrinsically Compliant Humanoid Robots
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Conference paperCarrera A, Carreras M, Kormushev P, et al., 2013,
Towards valve turning with an AUV using Learning by Demonstration
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Conference paperKryczka P, Kormushev P, Hashimoto K, et al., 2013,
Hybrid gait pattern generator capable of rapid and dynamically consistent pattern regeneration
, Publisher: IEEE, Pages: 475-480 -
Conference paperKryczka P, Shiguematsu YM, Kormushev P, et al., 2013,
Towards dynamically consistent real-time gait pattern generation for full-size humanoid robots
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Journal articleKormushev P, Calinon S, Caldwell DG, 2013,
Reinforcement Learning in Robotics: Applications and Real-World Challenges
, Robotics, Vol: 2, Pages: 122-148, ISSN: 2218-6581 -
Conference paperDallali H, Mosadeghzad M, Medrano-Cerda GA, et al., 2013,
Development of a dynamic simulator for a compliant humanoid robot based on a symbolic multibody approach
, Pages: 598-603 -
Conference paperKormushev P, Caldwell DG, 2012,
Direct policy search reinforcement learning based on particle filtering
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Journal articleColasanto L, Kormushev P, Tsagarakis N, et al., 2012,
Optimization of a compact model for the compliant humanoid robot COMAN using reinforcement learning
, International Journal of Cybernetics and Information Technologies, Vol: 12, Pages: 76-85, ISSN: 1311-9702COMAN is a compliant humanoid robot. The introduction of passive compliance in some of its joints affects the dynamics of the whole system. Unlike traditional stiff robots, there is a deflection of the joint angle with respect to the desired one whenever an external torque is applied. Following a bottom up approach, the dynamic equations of the joints are defined first. Then, a new model which combines the inverted pendulum approach with a three-dimensional (Cartesian) compliant model at the level of the center of mass is proposed. This compact model is based on some assumptions that reduce the complexity but at the same time affect the precision. To address this problem, additional parameters are inserted in the model equation and an optimization procedure is performed using reinforcement learning. The optimized model is experimentally validated on the COMAN robot using several ZMP-based walking gaits.
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Conference paperKormushev P, Caldwell DG, 2012,
Simultaneous discovery of multiple alternative optimal policies by reinforcement learning
, Pages: 202-207
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