Modeling, Estimation, and Control of Robot-Soil Interactions
This thesis presents the development of hardware, theory, and experimental methods to enable a robotic manipulator arm to interact with soils and estimate soil properties from interaction forces. Unlike the majority of robotic systems interacting with soil, our objective is parameter estimation, not...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/7075 |
| _version_ | 1826215967033655296 |
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| author | Hong, Won |
| author_facet | Hong, Won |
| author_sort | Hong, Won |
| collection | MIT |
| description | This thesis presents the development of hardware, theory, and experimental methods to enable a robotic manipulator arm to interact with soils and estimate soil properties from interaction forces. Unlike the majority of robotic systems interacting with soil, our objective is parameter estimation, not excavation. To this end, we design our manipulator with a flat plate for easy modeling of interactions. By using a flat plate, we take advantage of the wealth of research on the similar problem of earth pressure on retaining walls. There are a number of existing earth pressure models. These models typically provide estimates of force which are in uncertain relation to the true force. A recent technique, known as numerical limit analysis, provides upper and lower bounds on the true force. Predictions from the numerical limit analysis technique are shown to be in good agreement with other accepted models. Experimental methods for plate insertion, soil-tool interface friction estimation, and control of applied forces on the soil are presented. In addition, a novel graphical technique for inverting the soil models is developed, which is an improvement over standard nonlinear optimization. This graphical technique utilizes the uncertainties associated with each set of force measurements to obtain all possible parameters which could have produced the measured forces. The system is tested on three cohesionless soils, two in a loose state and one in a loose and dense state. The results are compared with friction angles obtained from direct shear tests. The results highlight a number of key points. Common assumptions are made in soil modeling. Most notably, the Mohr-Coulomb failure law and perfectly plastic behavior. In the direct shear tests, a marked dependence of friction angle on the normal stress at low stresses is found. This has ramifications for any study of friction done at low stresses. In addition, gradual failures are often observed for vertical tools and tools inclined away from the direction of motion. After accounting for the change in friction angle at low stresses, the results show good agreement with the direct shear values. |
| first_indexed | 2024-09-23T16:40:16Z |
| id | mit-1721.1/7075 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T16:40:16Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/70752019-04-10T11:52:32Z Modeling, Estimation, and Control of Robot-Soil Interactions Hong, Won AI Robotics Soil Modeling This thesis presents the development of hardware, theory, and experimental methods to enable a robotic manipulator arm to interact with soils and estimate soil properties from interaction forces. Unlike the majority of robotic systems interacting with soil, our objective is parameter estimation, not excavation. To this end, we design our manipulator with a flat plate for easy modeling of interactions. By using a flat plate, we take advantage of the wealth of research on the similar problem of earth pressure on retaining walls. There are a number of existing earth pressure models. These models typically provide estimates of force which are in uncertain relation to the true force. A recent technique, known as numerical limit analysis, provides upper and lower bounds on the true force. Predictions from the numerical limit analysis technique are shown to be in good agreement with other accepted models. Experimental methods for plate insertion, soil-tool interface friction estimation, and control of applied forces on the soil are presented. In addition, a novel graphical technique for inverting the soil models is developed, which is an improvement over standard nonlinear optimization. This graphical technique utilizes the uncertainties associated with each set of force measurements to obtain all possible parameters which could have produced the measured forces. The system is tested on three cohesionless soils, two in a loose state and one in a loose and dense state. The results are compared with friction angles obtained from direct shear tests. The results highlight a number of key points. Common assumptions are made in soil modeling. Most notably, the Mohr-Coulomb failure law and perfectly plastic behavior. In the direct shear tests, a marked dependence of friction angle on the normal stress at low stresses is found. This has ramifications for any study of friction done at low stresses. In addition, gradual failures are often observed for vertical tools and tools inclined away from the direction of motion. After accounting for the change in friction angle at low stresses, the results show good agreement with the direct shear values. 2004-10-20T20:28:24Z 2004-10-20T20:28:24Z 2001-09-01 AITR-2001-007 http://hdl.handle.net/1721.1/7075 en_US AITR-2001-007 225 p. 66603884 bytes 4629577 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | AI Robotics Soil Modeling Hong, Won Modeling, Estimation, and Control of Robot-Soil Interactions |
| title | Modeling, Estimation, and Control of Robot-Soil Interactions |
| title_full | Modeling, Estimation, and Control of Robot-Soil Interactions |
| title_fullStr | Modeling, Estimation, and Control of Robot-Soil Interactions |
| title_full_unstemmed | Modeling, Estimation, and Control of Robot-Soil Interactions |
| title_short | Modeling, Estimation, and Control of Robot-Soil Interactions |
| title_sort | modeling estimation and control of robot soil interactions |
| topic | AI Robotics Soil Modeling |
| url | http://hdl.handle.net/1721.1/7075 |
| work_keys_str_mv | AT hongwon modelingestimationandcontrolofrobotsoilinteractions |