Localization Performance Improvement of a Low-Resolution Robotic System using an Electro-Permanent Magnetic Interface and an Ensemble Kalman Filter
| dc.contributor.author | Martin, Jacob Ryan | en |
| dc.contributor.committeechair | Komendera, Erik | en |
| dc.contributor.committeemember | Southward, Steve C. | en |
| dc.contributor.committeemember | Asbeck, Alan T. | en |
| dc.contributor.department | Mechanical Engineering | en |
| dc.date.accessioned | 2022-10-18T08:00:09Z | en |
| dc.date.available | 2022-10-18T08:00:09Z | en |
| dc.date.issued | 2022-10-17 | en |
| dc.description.abstract | As the United States is on the cusp of returning astronauts to the Moon, it becomes increasingly apparent that the assembly of structures in space will have to rely upon robots to perform the construction process. With a focus on sustaining a presence on the Moon's surface in such a harsh and unforgiving environment, demonstrating the robustness of autonomous assembly and capabilities of robotic manipulators is necessary. Current robotic assembly on Earth consists mainly of inspection or highly controlled environments, and always with a human in the loop to step in and fix issues if a problem occurs. To remove the human element, the robot system then must account for safety as well. Thus, system risk can easily overwhelm project costs. This thesis proposes a combination of hardware and state estimation solutions to improve the feasibility of low-fidelity and low-resolution robots for precision assembly tasks. Doing so reduces the risk to mission success, as the hardware becomes easier to replace or repair. The hardware modifications implement an electro-permanent magnet interface with alignment features to reduce the fidelity needed for the robot end effector. On the state estimation side, an Ensemble Kalman Filter is implemented, along with a scaling system to prevent FASER Lab hardware from becoming stuck due to hardware limitations. Overall, the three modifications improved the test robot's autonomous convergence error by 98.5%, bettering the system sufficiently to make an autonomous assembly process feasible. | en |
| dc.description.abstractgeneral | With the dawn of new space age nearly upon us, one of the most important aspects to working in space will be robotic assembly, whether on the surface of other planetary bodies like the Moon or in zero-gravity, in order to keep astronauts safe and to reduce spaceship launch costs. Both places have their own difficult problems to deal with, and doing any actions in those locations come with a significant amount of risk involved. To reduce extreme risk, you can spend more money to over-protect the robots, or reduce the consequences of the risk. This thesis describes a way to reduce the impact of risks to a mission by checking whether inexpensive robots can be adapted and modified to be able to perform similar construction actions to a much more expensive robot. It does this by using specialized hardware and software programs to better align the robot to where it needs to go without people needing to step in and help it. The experiments showed a 98.5% improvement to the system from without any of the modifications and validated that the low-cost robot could be improved sufficiently to be useful. | en |
| dc.description.degree | Master of Science | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:35670 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/112183 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | In-space Assembly | en |
| dc.subject | Autonomous Robotics | en |
| dc.subject | Low-Resolution | en |
| dc.title | Localization Performance Improvement of a Low-Resolution Robotic System using an Electro-Permanent Magnetic Interface and an Ensemble Kalman Filter | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Mechanical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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