Abstract

The cable-driven hyper-redundant snake-like manipulator (CHSM) inspired by the biomimetic structure of vertebrate muscles and tendons, which consists of numerous joint units connected adjacently driven by elastic materials with hyper-redundant DOF, performs flexible kinematic skills and competitive compound capability under complicated working circumstances. Nevertheless, the drawback of lacking the ability to perceive the environment to perform intelligently in complex scenarios leaves a lot to be improved, which is the original intention to introduce visual tracking feedback acting as an instructor. In this paper, a cable-driven snake-like robotic arm combined with a visual tracking technique is introduced. A visual tracking approach based on dual correlation filter is designed to guide the CHSM in detecting the target and tracing after its trajectory. Specifically, it contains an adaptive optimization for the scale variation of the tracking target via pyramid sampling. For the CHSM, an explicit kinematics model is derived from its specific geometry relationships and followed by a simplification for the inverse kinematics based on some assumption or limitation. A control scheme is brought up to combine the kinematics with visual tracking via the processing tracking errors. The experimental results with a practical prototype validate the availability of the proposed compound control method with the derived kinematics model.

Highlights

  • Robotic arms have been widely developed in the industrial manufactured application and gradually reduced human participation since the first sophisticated robotic arm was designed by da Vinci in 1495

  • There is a definite trend in the manufacture of robotic arms toward more dexterous devices, more degrees of freedom (DOF), and capabilities beyond the human arm [1]

  • Cable-driven hyper-redundant snake-like manipulator (CHSM) which has numerous joint units connected adjacently driven by elastic cables with hyper-redundant DOF can achieve the desired positions with different postures [4], which means the flexible motion and good obstacle avoidance capability under complicated working circumstances [5]

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Summary

Introduction

Robotic arms have been widely developed in the industrial manufactured application and gradually reduced human participation since the first sophisticated robotic arm was designed by da Vinci in 1495. Cable-driven hyper-redundant snake-like manipulator (CHSM) which has numerous joint units connected adjacently driven by elastic cables with hyper-redundant DOF can achieve the desired positions with different postures [4], which means the flexible motion and good obstacle avoidance capability under complicated working circumstances [5]. Since the snake-like manipulator has different kinematic and dynamic behaviors from traditional rigid robots, it is worthy to develop a visual servo system that can improve stability and precision for controlling [10]. Considering the advantage of cable-driven snake-like manipulator, visual tracking is recommended as an assistant target-oriented method for guiding the CHSM to lock on mission objectives under tasks such as salvage or rescue, especially in the scenarios such as narrow and tortuous caverns or pipelines.

Implementation of Tracking Component
Translation Filter
Multi-Channel Features
Adaptive Scale
Tracking by Detection
Learning and Update
Overall Structure Design of CHSM
E N similarly to
Inverse Kinematics
Control Method
Experiment and Validation
Conclusion
Full Text
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