Planning locomotion trajectories for legged microrobots is challenging. This is because of their complex morphology, high frequency passive dynamics, and discontinuous contact interactions with their environment. Consequently, such research is often driven by time-consuming experimental methods. As an alternative, we present a framework for systematically modeling, planning, and controlling legged microrobots. We develop a three- dimensional dynamic model of a 1.5 g quadrupedal microrobot with complexity (e.g., number of degrees of freedom) similar to larger-scale legged robots. We then adapt a recently developed variational contact-implicit trajectory optimization method to generate feasible whole-body locomotion plans for this microrobot, and demonstrate that these plans can be tracked with simple joint-space controllers. We plan and execute periodic gaits at multiple stride frequencies and on various surfaces. These gaits achieve high per-cycle velocities, including a maximum of 10.87 mm/cycle, which is 15% faster than previously measured for this microrobot. Furthermore, we plan and execute a vertical jump of 9.96 mm, which is 78% of the microrobot’s center-of- mass height. To the best of our knowledge, this is the first end-to-end demonstration of planning and tracking whole-body dynamic locomotion on a millimeter-scale legged microrobot.
Papers with video attachments
Contact-Implicit Optimization of Locomotion Trajectories for a Quadrupedal Microrobot,” in Robotics: Science and Systems (RSS), 2018.Abstract
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Human-in-the-loop optimization of hip assistance with a soft exosuit during walking,” Science Robotics, vol. 3, no. 15, pp. eaar5438, 2018. Publisher's VersionAbstract
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DIRTREL: Robust Trajectory Optimization with Ellipsoidal Disturbances and LQR Feedback,” in Robotics: Science and Systems (RSS), 2017.Abstract
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Director: A User Interface Designed for Robot Operation with Shared Autonomy,” Journal of Field Robotics, 2016.Abstract
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Optimization-based locomotion planning, estimation, and control design for Atlas,” Autonomous Robots, vol. 40, no. 3, pp. 429–455, 2016.Abstract
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Optimization and stabilization of trajectories for constrained dynamical systems,” in Proceedings of the International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.Abstract
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An Architecture for Online Affordance-based Perception and Whole-body Planning,” Journal of Field Robotics, vol. 32, no. 2, pp. 229–254, 2015.Abstract
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An Efficiently Solvable Quadratic Program for Stabilizing Dynamic Locomotion,” in Proceedings of the International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014, pp. 2589–2594.Abstract
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A summary of team MIT's approach to the virtual robotics challenge,” in Robotics and Automation (ICRA), 2014 IEEE International Conference on, 2014, pp. 2087–2087.Abstract
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Variable Risk Control via Stochastic Optimization,” International Journal of Robotics Research, vol. 32, no. 7, pp. 806–825, 2013.Abstract
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Variable Risk Dynamic Mobile Manipulation,” in RSS 2012 Workshop on Mobile Manipulation, Sydney, Australia, 2012.Abstract
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Variational Bayesian Optimization for Runtime Risk-Sensitive Control,” in Robotics: Science and Systems VIII (RSS), Sydney, Australia, 2012, pp. 201–206.Abstract
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Robot learning from demonstration by constructing skill trees,” The International Journal of Robotics Research, vol. 31, no. 3, pp. 360–375, 2012.Abstract
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Autonomous Skill Acquisition on a Mobile Manipulator,” in Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI-11), San Francisco, CA, 2011, pp. 1468–1473.Abstract
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Learning Dynamic Arm Motions for Postural Recovery,” in Proceedings of the 11th IEEE-RAS International Conference on Humanoid Robots, Bled, Slovenia, 2011, pp. 7–12.Abstract
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