Multiple-Target Homotopic Quasi-Complete Path Planning Method for Mobile Robot Using a Piecewise Linear Approach.

Area of Science:

• Robotics
• Artificial Intelligence
• Computer Science

Background:

• Autonomous mobile robots require efficient multiple-target path planning for industrial tasks like inspection and service.
• Existing point-to-point strategies for collision-free path planning are often inefficient, leading to suboptimal path lengths.

Purpose of the Study:

• To present a novel multiple-target, collision-free path planning method based on homotopy continuation.
• To enhance the performance and robustness of existing homotopic path planning methods.

Main Methods:

• A new method utilizing homotopy continuation, Double Spherical Tracking (DST), a dummy obstacle scheme, and a systematic repulsion parameter selection.
• Comparison with sampling-based planning algorithms (SBP) and validation through MATLAB simulations.

Main Results:

• The proposed method achieves significantly better performance in speed, efficiency, and robustness compared to the original Homotopic Path Planning Method (HPPM).
• Case studies demonstrate effective path planning in complex, office-like environments with numerous obstacles and narrow corridors in milliseconds.
• The method outperforms SBP algorithms in execution time, memory usage, and often path length.

Conclusions:

• The developed homotopy continuation method offers a superior solution for multiple-target collision-free path planning in complex environments.
• The planner's feasibility is validated through simulations with differential drive robot models.