{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/78765"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/78765","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Damage Reduction Strategies for a Falling Humanoid Robot","abstract":"Instability of humanoid robots is a common problem, especially given external disturbances or difficult terrain. Even with the robustness of most whole body controllers, instability is inevitable given the right conditions. When these unstable events occur they can result in costly damage to the robot potentially causing a cease of normal functionality. Therefore, it is important to study and develop methods to control a humanoid robot during a fall to reduce the chance of critical damage. This thesis proposes joint angular velocity strategies to reduce the impact velocity resulting from a lateral, backward, or forward fall. These strategies were used on two and three link reduced order models to simulate a fall from standing height of a humanoid robot. The results of these simulations were then used on a full degree of freedom robot, Viginia Tech's humanoid robot ESCHER, to validate the efficacy of these strategies. By using angular velocity strategies for the knee and waist joint, the reduced order models resulted in a decrease in impact velocity of the center of mass by 58%, 87%, and 74% for a lateral, backward, and forward fall respectively in comparison to a rigid fall using the same initial conditions. Best case angular velocity strategies were then developed for various initial conditions for each falling direction. Finally, these parameters were implemented on the full degree of freedom robot which showed results similar to those of the reduced order models.","abstract_html":"Instability of humanoid robots is a common problem, especially given external disturbances or difficult terrain. Even with the robustness of most whole body controllers, instability is inevitable given the right conditions. When these unstable events occur they can result in costly damage to the robot potentially causing a cease of normal functionality. Therefore, it is important to study and develop methods to control a humanoid robot during a fall to reduce the chance of critical damage. This thesis proposes joint angular velocity strategies to reduce the impact velocity resulting from a lateral, backward, or forward fall. These strategies were used on two and three link reduced order models to simulate a fall from standing height of a humanoid robot. The results of these simulations were then used on a full degree of freedom robot, Viginia Tech's humanoid robot ESCHER, to validate the efficacy of these strategies. By using angular velocity strategies for the knee and waist joint, the reduced order models resulted in a decrease in impact velocity of the center of mass by 58%, 87%, and 74% for a lateral, backward, and forward fall respectively in comparison to a rigid fall using the same initial conditions. Best case angular velocity strategies were then developed for various initial conditions for each falling direction. Finally, these parameters were implemented on the full degree of freedom robot which showed results similar to those of the reduced order models.","abstract_has_math":false,"creators":["Amico, Peter joseph"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Furukawa, Tomonari","Lattimer, Brian Y."],"committee_members":["Asbeck, Alan T.","Leonessa, Alexander"],"year":2017,"date_issued":"2017-08-29","date_published":"2017-08-29","updated_at":"2026-07-22T22:18:41Z","subjects":["Humanoid","Robot","Falling","Falling Strategies","Impact Reduction"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:12767"],"render_values":[{"text":"vt_gsexam:12767","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/78765","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Furukawa, Tomonari","Lattimer, Brian Y."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Asbeck, Alan T.","Leonessa, Alexander"]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Amico, Peter joseph"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-08-30T08:00:32Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-08-30T08:00:32Z"]},{"key":"dc:date.issued","label":"Date","values":["2017-08-29"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Humanoid","Robot","Falling","Falling Strategies","Impact Reduction"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:12767"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/78765"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Instability of humanoid robots is a common problem, especially given external disturbances or difficult terrain. Even with the robustness of most whole body controllers, instability is inevitable given the right conditions. When these unstable events occur they can result in costly damage to the robot potentially causing a cease of normal functionality. Therefore, it is important to study and develop methods to control a humanoid robot during a fall to reduce the chance of critical damage. This thesis proposes joint angular velocity strategies to reduce the impact velocity resulting from a lateral, backward, or forward fall. These strategies were used on two and three link reduced order models to simulate a fall from standing height of a humanoid robot. The results of these simulations were then used on a full degree of freedom robot, Viginia Tech's humanoid robot ESCHER, to validate the efficacy of these strategies. By using angular velocity strategies for the knee and waist joint, the reduced order models resulted in a decrease in impact velocity of the center of mass by 58%, 87%, and 74% for a lateral, backward, and forward fall respectively in comparison to a rigid fall using the same initial conditions. Best case angular velocity strategies were then developed for various initial conditions for each falling direction. Finally, these parameters were implemented on the full degree of freedom robot which showed results similar to those of the reduced order models."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["Instability of humanoid robots is a common problem, especially given external disturbances or difficult terrain. Even with the robustness of most whole body controllers, instability is inevitable given the right conditions. When these unstable events occur they can result in costly damage to the robot potentially causing a cease of normal functionality. Therefore, it is important to study and develop methods to control a humanoid robot during a fall to reduce the chance of critical damage. This thesis proposes strategies that rotate the joints at a constant rate to reduce damage resulting from a lateral, backward, or forward fall. These strategies were used on two and three link simplistic models to simulate a fall from standing height of a humanoid robot. The results of these simulations were then used on a full robot, Viginia Tech’s humanoid robot ESCHER, to validate the efficacy of these strategies. By constant joint rotation strategies for the knee and waist joint, the simplistic models resulted in a decrease in impact velocity of the center of mass by 58%, 87%, and 74% for a lateral, backward, and forward fall respectively in comparison to a rigid fall using the same initial conditions. Best case joint rotation strategies were then developed for various initial conditions for each falling direction. 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Even with the robustness of most whole body controllers, instability is inevitable given the right conditions. When these unstable events occur they can result in costly damage to the robot potentially causing a cease of normal functionality. Therefore, it is important to study and develop methods to control a humanoid robot during a fall to reduce the chance of critical damage. This thesis proposes joint angular velocity strategies to reduce the impact velocity resulting from a lateral, backward, or forward fall. These strategies were used on two and three link reduced order models to simulate a fall from standing height of a humanoid robot. The results of these simulations were then used on a full degree of freedom robot, Viginia Tech's humanoid robot ESCHER, to validate the efficacy of these strategies. By using angular velocity strategies for the knee and waist joint, the reduced order models resulted in a decrease in impact velocity of the center of mass by 58%, 87%, and 74% for a lateral, backward, and forward fall respectively in comparison to a rigid fall using the same initial conditions. Best case angular velocity strategies were then developed for various initial conditions for each falling direction. Finally, these parameters were implemented on the full degree of freedom robot which showed results similar to those of the reduced order models."],"dc:description.abstractgeneral":["Instability of humanoid robots is a common problem, especially given external disturbances or difficult terrain. Even with the robustness of most whole body controllers, instability is inevitable given the right conditions. When these unstable events occur they can result in costly damage to the robot potentially causing a cease of normal functionality. Therefore, it is important to study and develop methods to control a humanoid robot during a fall to reduce the chance of critical damage. This thesis proposes strategies that rotate the joints at a constant rate to reduce damage resulting from a lateral, backward, or forward fall. These strategies were used on two and three link simplistic models to simulate a fall from standing height of a humanoid robot. The results of these simulations were then used on a full robot, Viginia Tech’s humanoid robot ESCHER, to validate the efficacy of these strategies. By constant joint rotation strategies for the knee and waist joint, the simplistic models resulted in a decrease in impact velocity of the center of mass by 58%, 87%, and 74% for a lateral, backward, and forward fall respectively in comparison to a rigid fall using the same initial conditions. Best case joint rotation strategies were then developed for various initial conditions for each falling direction. Finally, these parameters were implemented on the full robot which showed results similar to those of the reduced order models."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:12767"],"dc:identifier.uri":["http://hdl.handle.net/10919/78765"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Humanoid","Robot","Falling","Falling Strategies","Impact Reduction"],"dc:title":["Damage Reduction Strategies for a Falling Humanoid Robot"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:18:41Z"}