Socially compliant robust navigation in crowded pedestrian environment
This thesis describes a robot navigation system that relies only on onboard sensors without a high-definition map to achieve real-time perception and planning in a crowded pedestrian environment. Integration of real-time perception and planning with interactive decision-making is the leading researc...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/157284 |
| _version_ | 1826121504264290304 |
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| author | Chen, Tairan |
| author2 | Wang Dan Wei |
| author_facet | Wang Dan Wei Chen, Tairan |
| author_sort | Chen, Tairan |
| collection | NTU |
| description | This thesis describes a robot navigation system that relies only on onboard sensors without a high-definition map to achieve real-time perception and planning in a crowded pedestrian environment. Integration of real-time perception and planning with interactive decision-making is the leading research focus of this project. The perception module detects the drivable area in real-time using a semantic segmentation network, estimates the state of surrounding pedestrians using an object detection and tracking network, and predicts the future state of pedestrians by a pedestrian prediction network. The planning module integrates the perception information and calculates the robot's trajectory. Two methods based on optimization and sampling are applied, and both planning performances are compared. We also develop a pedestrian simulator to verify the functionality of the navigation system and then deploy the navigation system on a real robot. Experiments show that the robot can easily handle common pedestrian navigation scenarios and even some more complex scenarios. |
| first_indexed | 2024-10-01T05:33:20Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/157284 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:33:20Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1572842023-07-04T17:47:51Z Socially compliant robust navigation in crowded pedestrian environment Chen, Tairan Wang Dan Wei School of Electrical and Electronic Engineering EDWWANG@ntu.edu.sg Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics This thesis describes a robot navigation system that relies only on onboard sensors without a high-definition map to achieve real-time perception and planning in a crowded pedestrian environment. Integration of real-time perception and planning with interactive decision-making is the leading research focus of this project. The perception module detects the drivable area in real-time using a semantic segmentation network, estimates the state of surrounding pedestrians using an object detection and tracking network, and predicts the future state of pedestrians by a pedestrian prediction network. The planning module integrates the perception information and calculates the robot's trajectory. Two methods based on optimization and sampling are applied, and both planning performances are compared. We also develop a pedestrian simulator to verify the functionality of the navigation system and then deploy the navigation system on a real robot. Experiments show that the robot can easily handle common pedestrian navigation scenarios and even some more complex scenarios. Master of Science (Computer Control and Automation) 2022-05-11T13:55:25Z 2022-05-11T13:55:25Z 2022 Thesis-Master by Coursework Chen, T. (2022). Socially compliant robust navigation in crowded pedestrian environment. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157284 https://hdl.handle.net/10356/157284 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Chen, Tairan Socially compliant robust navigation in crowded pedestrian environment |
| title | Socially compliant robust navigation in crowded pedestrian environment |
| title_full | Socially compliant robust navigation in crowded pedestrian environment |
| title_fullStr | Socially compliant robust navigation in crowded pedestrian environment |
| title_full_unstemmed | Socially compliant robust navigation in crowded pedestrian environment |
| title_short | Socially compliant robust navigation in crowded pedestrian environment |
| title_sort | socially compliant robust navigation in crowded pedestrian environment |
| topic | Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics |
| url | https://hdl.handle.net/10356/157284 |
| work_keys_str_mv | AT chentairan sociallycompliantrobustnavigationincrowdedpedestrianenvironment |