Quadratic Programming-Based Posture Manipulation and Thrust-vectoring for Agile Dynamic Walking on Narrow Pathways

Kavli Affiliate: Morteza Gharib

| First 5 Authors: Chenghao Wang, Chenghao Wang, , ,

| Summary:

There has been significant advancement in legged robot’s agility where they
can show impressive acrobatic maneuvers, such as parkour. These maneuvers rely
heavily on posture manipulation. To expand the stability and locomotion
plasticity, we use the multi-modal ability in our legged-aerial platform, the
Husky Beta, to perform thruster-assisted walking. This robot has thrusters on
each of its sagittal knee joints which can be used to stabilize its frontal
dynamic as it walks. In this work, we perform a simulation study of quadruped
narrow-path walking with Husky $beta$, where the robot will utilize its
thrusters to stably walk on a narrow path. The controller is designed based on
a centroidal dynamics model with thruster and foot ground contact forces as
inputs. These inputs are regulated using a QP solver to be used in a model
predictive control framework. In addition to narrow-path walking, we also
perform a lateral push-recovery simulation to study how the thrusters can be
used to stabilize the frontal dynamics.

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