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Smart Sensing and Adaptive Reasoning for Enabling Industrial Robots with Interactive Human-Robot Capabilities in
Jaime Zabalza1, Zixiang Fei2, Cuebong Wong3
1Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK. j.zabalza@strath.ac.uk.
Sensors (Basel, Switzerland)
|March 21, 2019
Summary
This study introduces smart sensing for robots, enabling real-time collision avoidance and adaptive path planning in dynamic manufacturing environments. This allows for safer, more flexible human-robot and robot-robot interactions.
Area of Science:
- Robotics
- Artificial Intelligence
- Manufacturing Systems
Background:
- Traditional manufacturing relies on repetitive robotic actions in fixed environments.
- Increasing demand for autonomous and flexible manufacturing in unstructured settings.
- Need for robots to adapt to dynamic, unpredictable conditions.
Purpose of the Study:
- To equip a robotic manipulator with smart sensing for real-time collision avoidance.
- To enable online path planning in dynamically-changing environments.
- To facilitate smooth human-robot and robot-robot interactions.
Main Methods:
- Implemented a KUKA KR90 R3100 robotic manipulator.
- Developed a machine vision module using low-cost cameras and HSV color detection.
- Integrated adaptive path planning and robot control modules for simultaneous operation.
Main Results:
- Successfully detected and localized randomly moving obstacles.
- Achieved real-time path correction for collision avoidance.
- Demonstrated reaction times below average human reaction time.
Conclusions:
- Smart sensing capabilities enable robots to interact smoothly with dynamic environments.
- Innovative integration of sensing, planning, and control facilitates effective human-robot collaboration.
- The system supports autonomous thinking and reasoning for robots in unpredictable settings.
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