Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot
This paper details the supporting of the development of a novel Simultaneous Localization and Mapping (SLAM) algorithm for autonomous delivery robots, emphasizing the need for a robust robotics testing platform. The research utilizes the NVIDIA Carter Robot, an open-source Robot Operating System...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/176138 |
| _version_ | 1811694148991844352 |
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| author | Ang, Samuel De Jie |
| author2 | Andy Khong W H |
| author_facet | Andy Khong W H Ang, Samuel De Jie |
| author_sort | Ang, Samuel De Jie |
| collection | NTU |
| description | This paper details the supporting of the development of a novel Simultaneous
Localization and Mapping (SLAM) algorithm for autonomous delivery robots,
emphasizing the need for a robust robotics testing platform. The research utilizes the
NVIDIA Carter Robot, an open-source Robot Operating System 2 (ROS2)-based
platform that aligns with the intended delivery robot in size and capabilities, as a
testbed for the proposed solution. The fusion of the data from LiDARs and multiple
depth sensors addresses the need for dynamic obstacle avoidance and path planning
in unseen environments.
The research encountered and addressed substantial hardware challenges, notably in
the synchronization of the drivetrain with the onboard computational unit—a critical
prerequisite for the robot's functional deployment. The need for multi-sensor and
multi-modal algorithms to be running simultaneously also introduced additional
complexities due to the limited data transfer bandwidth available. An integral
component of the research also entailed the meticulous calibration of the robot's
transformation in space within ROS to guarantee the efficacy of the SLAM
algorithms.
The results of this research demonstrate the feasibility of using multiple Intel
RealSense cameras, as well as the viability of advanced SLAM techniques in realworld scenarios, thereby paving the way for future innovations in robotic autonomy. |
| first_indexed | 2024-10-01T07:02:59Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/176138 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:02:59Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1761382024-05-18T16:53:39Z Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot Ang, Samuel De Jie Andy Khong W H Lum Guo Zhan School of Mechanical and Aerospace Engineering Delta-NTU Corporate Laboratory gzlum@ntu.edu.sg, AndyKhong@ntu.edu.sg Engineering This paper details the supporting of the development of a novel Simultaneous Localization and Mapping (SLAM) algorithm for autonomous delivery robots, emphasizing the need for a robust robotics testing platform. The research utilizes the NVIDIA Carter Robot, an open-source Robot Operating System 2 (ROS2)-based platform that aligns with the intended delivery robot in size and capabilities, as a testbed for the proposed solution. The fusion of the data from LiDARs and multiple depth sensors addresses the need for dynamic obstacle avoidance and path planning in unseen environments. The research encountered and addressed substantial hardware challenges, notably in the synchronization of the drivetrain with the onboard computational unit—a critical prerequisite for the robot's functional deployment. The need for multi-sensor and multi-modal algorithms to be running simultaneously also introduced additional complexities due to the limited data transfer bandwidth available. An integral component of the research also entailed the meticulous calibration of the robot's transformation in space within ROS to guarantee the efficacy of the SLAM algorithms. The results of this research demonstrate the feasibility of using multiple Intel RealSense cameras, as well as the viability of advanced SLAM techniques in realworld scenarios, thereby paving the way for future innovations in robotic autonomy. Bachelor's degree 2024-05-14T01:36:20Z 2024-05-14T01:36:20Z 2024 Final Year Project (FYP) Ang, S. D. J. (2024). Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176138 https://hdl.handle.net/10356/176138 en C166 application/pdf Nanyang Technological University |
| spellingShingle | Engineering Ang, Samuel De Jie Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot |
| title | Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot |
| title_full | Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot |
| title_fullStr | Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot |
| title_full_unstemmed | Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot |
| title_short | Integrating hardware and software for novel SLAM algorithm development on the ROS2-based NVIDIA Carter Robot |
| title_sort | integrating hardware and software for novel slam algorithm development on the ros2 based nvidia carter robot |
| topic | Engineering |
| url | https://hdl.handle.net/10356/176138 |
| work_keys_str_mv | AT angsamueldejie integratinghardwareandsoftwarefornovelslamalgorithmdevelopmentontheros2basednvidiacarterrobot |