The Study on Real-Time RRT-Based Path Planning for UAVs Using a STM32 Microcontroller

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Publicat a:Electronics vol. 14, no. 24 (2025), p. 4901-4917
Autor principal: Tsai Shang-En
Altres autors: Shih-Ming, Yang, Wei-Cheng, Sun
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MDPI AG
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024 7 |a 10.3390/electronics14244901  |2 doi 
035 |a 3286276598 
045 2 |b d20250101  |b d20251231 
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100 1 |a Tsai Shang-En  |u Department of Computer Science and Information Engineering, Chang Jung Christian University, Tainan City 711, Taiwan 
245 1 |a The Study on Real-Time RRT-Based Path Planning for UAVs Using a STM32 Microcontroller 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Real-time path planning for autonomous Unmanned Aerial Vehicles (UAVs) under strict hardware limitations remains a central challenge in embedded robotics. This study presents a refined Rapidly-Exploring Random Tree (RRT) algorithm implemented within an onboard embedded system based on a 32-bit STM32 microcontroller, demonstrating that real-time autonomous navigation can be achieved under low-power computation constraints. The proposed framework integrates a three-stage process—path pruning, Bézier curve smoothing, and iterative optimization—designed to minimize computational overhead while maintaining flight stability. By leveraging the STM32’s limited 72 MHz ARM Cortex-M3 core and 20 KB SRAM, the system performs all planning stages directly on the microcontroller without external computation. Experimental flight tests verify that the UAV can autonomously generate and follow smooth, collision-free trajectories across static obstacle fields with high tracking accuracy. The results confirm the feasibility of executing a full RRT-based planner on an STM32-class embedded platform, establishing a practical pathway for resource-efficient, onboard UAV autonomy. 
653 |a Microcontrollers 
653 |a Robotics 
653 |a Curves 
653 |a Computation 
653 |a Embedded systems 
653 |a Unmanned aerial vehicles 
653 |a Planning 
653 |a Optimization 
653 |a Altitude 
653 |a Trees 
653 |a Design 
653 |a Autonomous navigation 
653 |a Collision avoidance 
653 |a Algorithms 
653 |a Real time 
653 |a Path planning 
653 |a Efficiency 
653 |a Flight tests 
653 |a Autonomy 
700 1 |a Shih-Ming, Yang  |u Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan City 701, Taiwan 
700 1 |a Wei-Cheng, Sun  |u Department of Computer Science and Information Engineering, Chang Jung Christian University, Tainan City 711, Taiwan 
773 0 |t Electronics  |g vol. 14, no. 24 (2025), p. 4901-4917 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
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856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3286276598/fulltextwithgraphics/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
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