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A featureless approach for object detection and tracking in dynamic environments.

Mohammad Zohaib1, Muhammad Ahsan1, Mudassir Khan2

  • 1National Center of Robotics and Automation (NCRA), Department of Mechatronics and Control Engineering, University of Engineering and Technology Lahore, Lahore, Pakistan.

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Summary
This summary is machine-generated.

This study introduces an efficient ROS-based algorithm for mobile robots to map dynamic environments. It accurately detects and tracks moving objects using spatial-temporal locality, reducing computational complexity for real-time systems.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Vision

Background:

  • Mapping dynamic environments is crucial for mobile robot navigation.
  • Existing dynamic SLAM techniques face challenges with high computational complexity.
  • There is a need for efficient algorithms suitable for real-time embedded systems.

Purpose of the Study:

  • To present a ROS-based efficient algorithm for constructing dynamic maps.
  • To enable detection and tracking of moving objects without prior geometrical knowledge.
  • To reduce computational complexity for real-time mobile robot applications.

Main Methods:

  • Exploiting spatial-temporal locality for object detection and tracking.
  • Decoding sensory data into time-varying object boundaries to estimate trajectory.
  • Updating dynamic environment maps with lower time-complexity.
  • Utilizing robot's Field of View (FoV) for iterative updates.

Main Results:

  • The algorithm efficiently detects and tracks moving objects.
  • It achieves lower time-complexity for dynamic environment updates.
  • The number of moving objects in environment snapshots remains constant.
  • Validated on V-Rep simulations and real-life experiments.

Conclusions:

  • The proposed algorithm offers an efficient solution for dynamic environment mapping in mobile robotics.
  • It accurately detects and tracks objects under low sensor noise and acceptable object speeds.
  • The approach is suitable for real-time embedded systems, overcoming limitations of complex SLAM techniques.