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Learning from Observation Using Primitives
, 2004
"... This paper describes the use of task primitives in robot learning from observation. A framework has been developed that uses observed data to initially learn a task and then the agent goes on to increase its performance through repeated task performance (learning from practice). Data that is collect ..."
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Cited by 70 (5 self)
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This paper describes the use of task primitives in robot learning from observation. A framework has been developed that uses observed data to initially learn a task and then the agent goes on to increase its performance through repeated task performance (learning from practice). Data that is collected while a human performs a task is parsed into small parts of the task called primitives. Modules are created for each primitive that encode the movements required during the performance of the primitive, and when and where the primitives are performed. The feasibility of this method is currently being tested with agents that learn to play a virtual and an actual air hockey game. 1
Adaptive Calibration And Control Of 2d Monocular Visual Servo Systems
- in Proc. 5th IFAC Symp. Robot Control, SYROCO’97
, 1997
"... : For a majority of visual servo systems, accurate camera--robot calibration is essential for precision tasks, such as tracking time--varying end--effector trajectories in the image plane. This paper presents details of control--theoretic approaches to calibration of monocular visual servo systems i ..."
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Cited by 18 (0 self)
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: For a majority of visual servo systems, accurate camera--robot calibration is essential for precision tasks, such as tracking time--varying end--effector trajectories in the image plane. This paper presents details of control--theoretic approaches to calibration of monocular visual servo systems in the case of a planar robot with workspace perpendicular to the optical axis of the imaging system. An on--line adaptive calibration and control scheme is developed along with an associated stability and convergence theorem. A redundancy--based refinement of this scheme is proposed and important issues are isolated for future study. Mots Cl`es: adaptive control, robot control, calibration, redundant manipulators, robot vision 1. INTRODUCTION For a robotic system to succeed in general tasks under standard visual servo paradigms, it is necessary for the vision system to be adequately calibrated with respect to the robot and the environment. A variety of techniques have been developed for calc...
Learning from observation and practice at the action generation level
- in IEEE International Conference on Humanoid Robots, Karlsruhe and
, 2003
"... Abstract. For humanoid robots to be accepted as partners with humans they will be expected to learn quickly and adapt to environment changes in ways similar to humans. Within a single task there may be many things that can change as humans interact with the robot. The placement of items within the w ..."
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Cited by 9 (3 self)
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Abstract. For humanoid robots to be accepted as partners with humans they will be expected to learn quickly and adapt to environment changes in ways similar to humans. Within a single task there may be many things that can change as humans interact with the robot. The placement of items within the workspace, the physics of the environment, and the reaction of the human to the robot’s movements are some examples of the things which can vary during the interaction. This paper presents a method for humanoid robots to quickly learn new dynamic tasks from observing others and from practice. Ways in which the robot can adapt to the initial and slowly changing environment conditions are also described. Agents are given domain knowledge in the form of task primitives. A key element of our approach is to break learning problems up into as many simple learning problems as possible. This process of “divide and conquer ” is limited only by the measurements available to the robot. We present a case study of a humanoid robot learning to play air hockey. 1
c ○ World Scientific Publishing Company LEARNING TO ACT FROM OBSERVATION AND PRACTICE
"... We present a method for humanoid robots to quickly learn new dynamic tasks from observing others and from practice. Ways in which the robot can adapt to initial and also changing conditions are described. Agents are given domain knowledge in the form of task primitives. A key element of our approach ..."
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We present a method for humanoid robots to quickly learn new dynamic tasks from observing others and from practice. Ways in which the robot can adapt to initial and also changing conditions are described. Agents are given domain knowledge in the form of task primitives. A key element of our approach is to break learning problems up into as many simple learning problems as possible. We present a case study of a humanoid robot learning to play air hockey.
