Plot comparing the circular tracking errors of the three algorithms. by Xiaosong Liu (66661)

Plot comparing the circular angle tracking performances of the three algorithms. by Xiaosong Liu (66661)

Graph showing the tracking errors of the three control algorithms under noise. by Xiaosong Liu (66661)

Chart showing the target tracking performances of the three control algorithms under noise. by Xiaosong Liu (66661)

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

Trajectory tracking for psi in a ramp helix path. by Elisabeth Andarge Gedefaw (20308092)

Figures of NEXT STEPS IN THE DEVELOPMENT OF PCA-NN MODEL FOR THE IONOSPHERE: DIFFERENT PARAMETERS, REGIONS, NN ALGORITHMS AND IMPUT PARAMETERS by Sara Garcia (22419613)

3D trajectory tracking of a square wave path. by Elisabeth Andarge Gedefaw (20308092)

3D trajectory tracking of a spiral infinity path. by Elisabeth Andarge Gedefaw (20308092)

3D trajectory tracking of a ramp helix path. by Elisabeth Andarge Gedefaw (20308092)

The structure of FasterNext. by Junjie Lu (160350)

“…<div><p>The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under hardware resource constraints. …”

Summary of Experimental Setup, which presents the hardware configuration, model training parameters, and key settings for the path planning algorithm. by Yan Chen (4308)

Subjects:

Path Planning Module: Includes the full workflow of global path generation, local obstacle avoidance (APF), dynamic path adjustment (DDPG), and path smoothing optimization, as well... by Yan Chen (4308)

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Harmonic artificial potential field path planning for tracked robots in unstructured environments by Angelo Ugenti (22328960)

“…Using a real-case planetary exploration scenario, results demonstrate that the proposed algorithm provides a more comprehensive approach to path planning by taking into account various factors. …”

Workflow of the developed simulation algorithm. by Arnab Mutsuddy (22146227)

Parameters of the FasterNext and C3. by Junjie Lu (160350)

“…<div><p>The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under hardware resource constraints. …”

Excerpts from the raw acquired data set with the tracking algorithm. by Hannes Benecke (17409369)

Decision-Making and Control Module Architecture: This includes the collaborative workflow of path tracking and real-time optimization based on MPC, along with dynamic obstacle traj... by Yan Chen (4308)

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Comparison of detection results of different methods in FasterNext. by Junjie Lu (160350)

Final Path Smoothing Optimization: Step-by-step results of smoothing optimization applied to the adjusted path. It shows how the path becomes more continuous and efficient through... by Yan Chen (4308)

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