@article{bjelonic2020rolling,
  author    = {Bjelonic, Marko and
               Sankar, Prajish K. and
               Bellicoso, Carmine D and
               Vallery, Heike and
               Hutter, Marco},
  title     = {Rolling in the Deep - Hybrid Locomotion for Wheeled-Legged
               Robots using Online Trajectory Optimization},
  journal   = {IEEE Robotics and Automation Letters},
  volume    = {5},
  number    = {2},
  pages     = {3626-3633},
  doi       = {10.1109/LRA.2020.2979661},
  year      = {2020},
  abstract  = {Wheeled-legged robots have the potential for highly agile and
               versatile locomotion. The combination of legs and wheels might
               be a solution for any real-world application requiring rapid,
               and long-distance mobility skills on challenging terrain. In
               this paper, we present an online trajectory optimization
               framework for wheeled quadrupedal robots capable of executing
               hybrid walking-driving locomotion strategies. By breaking down
               the optimization problem into a wheel and base trajectory
               planning, locomotion planning for high dimensional
               wheeled-legged robots becomes more tractable, can be solved in
               real-time on-board in a model predictive control fashion, and
               becomes robust against unpredicted disturbances. The reference
               motions are tracked by a hierarchical whole-body controller that
               sends torque commands to the robot. Our approach is verified on
               a quadrupedal robot that is fully torque-controlled, including
               the non-steerable wheels attached to its legs. The robot
               performs hybrid locomotion with different gait sequences on flat
               and rough terrain. In addition, we validated the robotic
               platform at the Defense Advanced Research Projects Agency
               (DARPA) Subterranean Challenge, where the robot rapidly maps,
               navigates, and explores dynamic underground environments.},
  keywords  = {legged robots, wheeled robots,
               motion and path planning, optimization and optimal control},
  url_pdf   = {files/2020_ral_bjelonic.pdf},
  url_video = {https://youtu.be/ukY0vyM-yfY},
  url_link  = {https://ieeexplore.ieee.org/document/9028228},
  url_link  = {https://youtu.be/tf_twcbF4P4},
}

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K.","Bellicoso, C. D","Vallery, H.","Hutter, M."],"bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Bjelonic"],"firstnames":["Marko"],"suffixes":[]},{"propositions":[],"lastnames":["Sankar"],"firstnames":["Prajish","K."],"suffixes":[]},{"propositions":[],"lastnames":["Bellicoso"],"firstnames":["Carmine","D"],"suffixes":[]},{"propositions":[],"lastnames":["Vallery"],"firstnames":["Heike"],"suffixes":[]},{"propositions":[],"lastnames":["Hutter"],"firstnames":["Marco"],"suffixes":[]}],"title":"Rolling in the Deep - Hybrid Locomotion for Wheeled-Legged Robots using Online Trajectory Optimization","journal":"IEEE Robotics and Automation Letters","volume":"5","number":"2","pages":"3626-3633","doi":"10.1109/LRA.2020.2979661","year":"2020","abstract":"Wheeled-legged robots have the potential for highly agile and versatile locomotion. The combination of legs and wheels might be a solution for any real-world application requiring rapid, and long-distance mobility skills on challenging terrain. In this paper, we present an online trajectory optimization framework for wheeled quadrupedal robots capable of executing hybrid walking-driving locomotion strategies. By breaking down the optimization problem into a wheel and base trajectory planning, locomotion planning for high dimensional wheeled-legged robots becomes more tractable, can be solved in real-time on-board in a model predictive control fashion, and becomes robust against unpredicted disturbances. The reference motions are tracked by a hierarchical whole-body controller that sends torque commands to the robot. Our approach is verified on a quadrupedal robot that is fully torque-controlled, including the non-steerable wheels attached to its legs. The robot performs hybrid locomotion with different gait sequences on flat and rough terrain. In addition, we validated the robotic platform at the Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge, where the robot rapidly maps, navigates, and explores dynamic underground environments.","keywords":"legged robots, wheeled robots, motion and path planning, optimization and optimal control","url_pdf":"files/2020_ral_bjelonic.pdf","url_video":"https://youtu.be/ukY0vyM-yfY","url_link":"https://youtu.be/tf_twcbF4P4","bibtex":"@article{bjelonic2020rolling,\n author = {Bjelonic, Marko and\n Sankar, Prajish K. and\n Bellicoso, Carmine D and\n Vallery, Heike and\n Hutter, Marco},\n title = {Rolling in the Deep - Hybrid Locomotion for Wheeled-Legged\n Robots using Online Trajectory Optimization},\n journal = {IEEE Robotics and Automation Letters},\n volume = {5},\n number = {2},\n pages = {3626-3633},\n doi = {10.1109/LRA.2020.2979661},\n year = {2020},\n abstract = {Wheeled-legged robots have the potential for highly agile and\n versatile locomotion. The combination of legs and wheels might\n be a solution for any real-world application requiring rapid,\n and long-distance mobility skills on challenging terrain. In\n this paper, we present an online trajectory optimization\n framework for wheeled quadrupedal robots capable of executing\n hybrid walking-driving locomotion strategies. By breaking down\n the optimization problem into a wheel and base trajectory\n planning, locomotion planning for high dimensional\n wheeled-legged robots becomes more tractable, can be solved in\n real-time on-board in a model predictive control fashion, and\n becomes robust against unpredicted disturbances. The reference\n motions are tracked by a hierarchical whole-body controller that\n sends torque commands to the robot. Our approach is verified on\n a quadrupedal robot that is fully torque-controlled, including\n the non-steerable wheels attached to its legs. The robot\n performs hybrid locomotion with different gait sequences on flat\n and rough terrain. In addition, we validated the robotic\n platform at the Defense Advanced Research Projects Agency\n (DARPA) Subterranean Challenge, where the robot rapidly maps,\n navigates, and explores dynamic underground environments.},\n keywords = {legged robots, wheeled robots,\n motion and path planning, optimization and optimal control},\n url_pdf = {files/2020_ral_bjelonic.pdf},\n url_video = {https://youtu.be/ukY0vyM-yfY},\n url_link = {https://ieeexplore.ieee.org/document/9028228},\n url_link = {https://youtu.be/tf_twcbF4P4},\n}\n\n","author_short":["Bjelonic, M.","Sankar, P. K.","Bellicoso, C. D","Vallery, H.","Hutter, M."],"key":"bjelonic2020rolling","id":"bjelonic2020rolling","bibbaseid":"bjelonic-sankar-bellicoso-vallery-hutter-rollinginthedeephybridlocomotionforwheeledleggedrobotsusingonlinetrajectoryoptimization-2020","role":"author","urls":{" pdf":"https://www.markobjelonic.com//publications/files/2020_ral_bjelonic.pdf"," video":"https://youtu.be/ukY0vyM-yfY"," link":"https://youtu.be/tf_twcbF4P4"},"keyword":["legged robots","wheeled robots","motion and path planning","optimization and optimal control"],"metadata":{"authorlinks":{"bjelonic, m":"https://www.markobjelonic.com/publications/"}},"downloads":28},"bibtype":"article","biburl":"https://www.markobjelonic.com//publications/bibliography.bib","creationDate":"2019-09-17T16:31:58.218Z","downloads":36,"keywords":["legged robots","wheeled robots","motion and path planning","optimization and optimal control"],"search_terms":["rolling","deep","hybrid","locomotion","wheeled","legged","robots","using","online","trajectory","optimization","bjelonic","sankar","bellicoso","vallery","hutter"],"title":"Rolling in the Deep - Hybrid Locomotion for Wheeled-Legged Robots using Online Trajectory Optimization","year":2020,"dataSources":["SDvvW5t5q7zaELwe8","2XwegAmFdhPoE6K88","QJYg6RGvtGt3DAY9M","zxMAQW6E7NWHa4cSY"]}