A developmental constraint driven approach to developmental robotic hand-eye coordination

Chao, Fei; Lin, Haixiong; Jiang, Min; Zhou, Changle

doi:10.1109/robio.2012.6491237

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…So, we decided to use a multi-joint robotic arm as our writing actuator. Also, we had done several robotic arm control and hand-eye coordination research in our previous work 1, [35][36][37] ; this previous research is fundamental to our current work.…”

Section: Robotic Writing and Related Workmentioning

confidence: 99%

Robotic Free Writing of Chinese Characters via Human–Robot Interactions

Chao

Chen

Shen

et al. 2014

Int. J. Human. Robot.

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Implementation of robotic writing ability is recognized as a di±cult task, which involves complicated image processing and robotic control algorithms. This paper introduces a novel approach to robotic writing by using human-robot interactions. The method applies a motion sensing input device to capture a human demonstrator's arm trajectories, uses a gesture determination algorithm to extract a Chinese character's strokes from these trajectories, and employs noise¯ltering and curve¯tting methods to optimize the strokes. The approach displays real-time captured trajectories to the human demonstrator; therefore, the human demonstrator is able to adjust his/her gesture to achieve a better character writing e®ect. Then, our robot writes the human-gestured character by using the robotic arm's joint values. The inverse kinematics algorithm generates the joint values from the stroke trajectories. Experimental analysis shows that the proposed approach can allow a human to naturally and conveniently control the robot in order to write many Chinese characters. Additionally, this approach allows the robot to achieve a satisfactory writing quality for characters with a simple structure, with the potential to write more complex characters.

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Section: Robotic Writing and Related Workmentioning

confidence: 99%

Robotic Free Writing of Chinese Characters via Human–Robot Interactions

Chao

Chen

Shen

et al. 2014

Int. J. Human. Robot.

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“…However, this work is merely done in simulated environment. Our previous work is similar to [27,28], where we applied neural networks to control our robot to learn reaching.…”

Section: Background and Related Workmentioning

confidence: 99%

Learning Robotic Hand-eye Coordination Through a Developmental Constraint Driven Approach

Chao

Zhang

Lin

et al. 2013

Int. J. Autom. Comput.

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Abstract:The skill of robotic hand-eye coordination not only helps robots to deal with real time environment, but also affects the fundamental framework of robotic cognition. A number of approaches have been developed in the literature for construction of the robotic hand-eye coordination. However, several important features within infant developmental procedure have not been introduced into such approaches. This paper proposes a new method for robotic hand-eye coordination by imitating the developmental progress of human infants. The work employs a brain-like neural network system inspired by infant brain structure to learn hand-eye coordination, and adopts a developmental mechanism from psychology to drive the robot. The entire learning procedure is driven by developmental constraint: The robot starts to act under fully constrained conditions, when the robot learning system becomes stable, a new constraint is assigned to the robot. After that, the robot needs to act with this new condition again. When all the contained conditions have been overcome, the robot is able to obtain hand-eye coordination ability. The work is supported by experimental evaluation, which shows that the new approach is able to drive the robot to learn autonomously, and make the robot also exhibit developmental progress similar to human infants.

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