Dynamic Mapping and 3D Perception Using Voxel Grid and Modified Artificial Potential Fields for Indoor Locomotion
This paper proposes an advanced 3D indoor navigation system for a mobile robot. The proposed method integrates RTAB-Map with Voxel Grid Filters and Joint Probabilistic Data Association (JPDA) to generate surrounding environment map efficiency. Additionally, the local path planner combines pure pursu...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10974978/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850115706428850176 |
|---|---|
| author | Trihastuti Agustinah Yurid Eka Nugraha Aqil Rabbani Nurhadi Vincentius Charles Maynad |
| author_facet | Trihastuti Agustinah Yurid Eka Nugraha Aqil Rabbani Nurhadi Vincentius Charles Maynad |
| author_sort | Trihastuti Agustinah |
| collection | DOAJ |
| description | This paper proposes an advanced 3D indoor navigation system for a mobile robot. The proposed method integrates RTAB-Map with Voxel Grid Filters and Joint Probabilistic Data Association (JPDA) to generate surrounding environment map efficiency. Additionally, the local path planner combines pure pursuit with a modified Artificial Potential Field (APF) method to improve navigation capability. It generates steering commands and desired velocities and adjusts the attractive potential force equation to maintain balance and operational efficiency. This modification improves safety, pedestrian avoidance, and comfort by minimizing unnecessary rotations while ensuring smooth navigation. The proposed system improves the locomotion ability by reducing roll, pitch, and yaw fluctuations by approximately 30% compared to traditional APF methods. Voxel grid filtering enhances computational efficiency, reducing processing time per iteration by up to 73% - from 0.247 seconds (raw LiDAR) to 0.067 seconds (voxel size of 0.9) - while maintaining obstacle detection accuracy. The integration of JPDA ensures safe multi-target detection, with minimum safe distances of 0.94 meters from dynamic actors and a Threat Level Index (TLI) peaking at 0.24. In a scenario comparing two robots with different map knowledge, the robot with map knowledge reached the waypoint 20% faster, following an efficient path. However, despite lacking prior knowledge, the second robot reached the waypoint, demonstrating the system’s adaptability. These quantitative results confirm the proposed method’s capability to enhance safety, efficiency, and human comfort, making it suitable for real-time indoor navigation in dynamic environments. |
| format | Article |
| id | doaj-art-eb522a1b8aa04dbd9cf4742056d49171 |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-eb522a1b8aa04dbd9cf4742056d491712025-08-20T02:36:30ZengIEEEIEEE Access2169-35362025-01-0113712887130510.1109/ACCESS.2025.356348410974978Dynamic Mapping and 3D Perception Using Voxel Grid and Modified Artificial Potential Fields for Indoor LocomotionTrihastuti Agustinah0https://orcid.org/0000-0001-9328-5110Yurid Eka Nugraha1Aqil Rabbani Nurhadi2Vincentius Charles Maynad3https://orcid.org/0009-0000-0734-9019Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, East Java, IndonesiaDepartment of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, East Java, IndonesiaDepartment of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, East Java, IndonesiaDepartment of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, East Java, IndonesiaThis paper proposes an advanced 3D indoor navigation system for a mobile robot. The proposed method integrates RTAB-Map with Voxel Grid Filters and Joint Probabilistic Data Association (JPDA) to generate surrounding environment map efficiency. Additionally, the local path planner combines pure pursuit with a modified Artificial Potential Field (APF) method to improve navigation capability. It generates steering commands and desired velocities and adjusts the attractive potential force equation to maintain balance and operational efficiency. This modification improves safety, pedestrian avoidance, and comfort by minimizing unnecessary rotations while ensuring smooth navigation. The proposed system improves the locomotion ability by reducing roll, pitch, and yaw fluctuations by approximately 30% compared to traditional APF methods. Voxel grid filtering enhances computational efficiency, reducing processing time per iteration by up to 73% - from 0.247 seconds (raw LiDAR) to 0.067 seconds (voxel size of 0.9) - while maintaining obstacle detection accuracy. The integration of JPDA ensures safe multi-target detection, with minimum safe distances of 0.94 meters from dynamic actors and a Threat Level Index (TLI) peaking at 0.24. In a scenario comparing two robots with different map knowledge, the robot with map knowledge reached the waypoint 20% faster, following an efficient path. However, despite lacking prior knowledge, the second robot reached the waypoint, demonstrating the system’s adaptability. These quantitative results confirm the proposed method’s capability to enhance safety, efficiency, and human comfort, making it suitable for real-time indoor navigation in dynamic environments.https://ieeexplore.ieee.org/document/10974978/Locomotion abilitymobile robotmodified artificial potential fieldvoxel grid filters |
| spellingShingle | Trihastuti Agustinah Yurid Eka Nugraha Aqil Rabbani Nurhadi Vincentius Charles Maynad Dynamic Mapping and 3D Perception Using Voxel Grid and Modified Artificial Potential Fields for Indoor Locomotion IEEE Access Locomotion ability mobile robot modified artificial potential field voxel grid filters |
| title | Dynamic Mapping and 3D Perception Using Voxel Grid and Modified Artificial Potential Fields for Indoor Locomotion |
| title_full | Dynamic Mapping and 3D Perception Using Voxel Grid and Modified Artificial Potential Fields for Indoor Locomotion |
| title_fullStr | Dynamic Mapping and 3D Perception Using Voxel Grid and Modified Artificial Potential Fields for Indoor Locomotion |
| title_full_unstemmed | Dynamic Mapping and 3D Perception Using Voxel Grid and Modified Artificial Potential Fields for Indoor Locomotion |
| title_short | Dynamic Mapping and 3D Perception Using Voxel Grid and Modified Artificial Potential Fields for Indoor Locomotion |
| title_sort | dynamic mapping and 3d perception using voxel grid and modified artificial potential fields for indoor locomotion |
| topic | Locomotion ability mobile robot modified artificial potential field voxel grid filters |
| url | https://ieeexplore.ieee.org/document/10974978/ |
| work_keys_str_mv | AT trihastutiagustinah dynamicmappingand3dperceptionusingvoxelgridandmodifiedartificialpotentialfieldsforindoorlocomotion AT yuridekanugraha dynamicmappingand3dperceptionusingvoxelgridandmodifiedartificialpotentialfieldsforindoorlocomotion AT aqilrabbaninurhadi dynamicmappingand3dperceptionusingvoxelgridandmodifiedartificialpotentialfieldsforindoorlocomotion AT vincentiuscharlesmaynad dynamicmappingand3dperceptionusingvoxelgridandmodifiedartificialpotentialfieldsforindoorlocomotion |