Quadrupedal walking motion and footstep placement through Linear Model Predictive Control

The present work addresses the generation of a walking gait with automatic footstep placement for a quadrupedal robot, within a Linear Model Predictive Control framework. Existing work has shown how this is only possible within a non-convex programming framework, finding a solution of which is well-...

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Published in:2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) pp. 2267 - 2273
Main Authors: Laurenzi, Arturo, Hoffman, Enrico Mingo, Tsagarakis, Nikos G.
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2018
Subjects:
Legged locomotion
Optimization
Planning
Robot kinematics
Stability analysis
ISSN:2153-0866
Online Access:Get full text
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Abstract The present work addresses the generation of a walking gait with automatic footstep placement for a quadrupedal robot, within a Linear Model Predictive Control framework. Existing work has shown how this is only possible within a non-convex programming framework, finding a solution of which is well-known to be very hard. We propose a way to formulate the joint optimization problem as an approximate QP with linear constraints, whose global optimum can be quickly found with off-the-shelf solvers. More specifically, this is done by introducing auxiliary states and control inputs, each of which is subject to linear constraints that are inspired from the literature on bipedal locomotion. Finally, we validate our method on the CENTAURO robot, a hybrid wheeled-legged quadruped with a humanoid upper-body.
AbstractList The present work addresses the generation of a walking gait with automatic footstep placement for a quadrupedal robot, within a Linear Model Predictive Control framework. Existing work has shown how this is only possible within a non-convex programming framework, finding a solution of which is well-known to be very hard. We propose a way to formulate the joint optimization problem as an approximate QP with linear constraints, whose global optimum can be quickly found with off-the-shelf solvers. More specifically, this is done by introducing auxiliary states and control inputs, each of which is subject to linear constraints that are inspired from the literature on bipedal locomotion. Finally, we validate our method on the CENTAURO robot, a hybrid wheeled-legged quadruped with a humanoid upper-body.
Author Hoffman, Enrico Mingo
Tsagarakis, Nikos G.
Laurenzi, Arturo
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  surname: Laurenzi
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  givenname: Enrico Mingo
  surname: Hoffman
  fullname: Hoffman, Enrico Mingo
  organization: Advanced Robotics Department (ADVR), Istituto Italiano di Tecnologia, Genova, Italy
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  givenname: Nikos G.
  surname: Tsagarakis
  fullname: Tsagarakis, Nikos G.
  organization: Advanced Robotics Department (ADVR), Istituto Italiano di Tecnologia, Genova, Italy
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Snippet The present work addresses the generation of a walking gait with automatic footstep placement for a quadrupedal robot, within a Linear Model Predictive Control...
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SubjectTerms Legged locomotion
Optimization
Planning
Robot kinematics
Stability analysis
Title Quadrupedal walking motion and footstep placement through Linear Model Predictive Control
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