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Learning-based legged locomotion: State of the art and future perspectives
Legged locomotion holds the premise of universal mobility, a critical capability for many real-
world robotic applications. Both model-based and learning-based approaches have …
world robotic applications. Both model-based and learning-based approaches have …
Optimization-based control for dynamic legged robots
In a world designed for legs, quadrupeds, bipeds, and humanoids have the opportunity to
impact emerging robotics applications from logistics, to agriculture, to home assistance. The …
impact emerging robotics applications from logistics, to agriculture, to home assistance. The …
Robust convex model predictive control for quadruped locomotion under uncertainties
This article considers quadruped locomotion control in the presence of uncertainties. Two
types of structured uncertainties are considered, namely, uncertain friction constraints and …
types of structured uncertainties are considered, namely, uncertain friction constraints and …
Layered control for cooperative locomotion of two quadrupedal robots: Centralized and distributed approaches
This article presents a layered control approach for real-time trajectory planning and control
of robust cooperative locomotion by two holonomically constrained quadrupedal robots. A …
of robust cooperative locomotion by two holonomically constrained quadrupedal robots. A …
Learning agile locomotion and adaptive behaviors via rl-augmented mpc
In the context of legged robots, adaptive behavior involves adaptive balancing and adaptive
swing foot reflection. While adaptive balancing counteracts perturbations to the robot …
swing foot reflection. While adaptive balancing counteracts perturbations to the robot …
Task-driven hybrid model reduction for dexterous manipulation
In contact-rich tasks, like dexterous manipulation, the hybrid nature of making and breaking
contact creates challenges for model representation and control. For example, choosing and …
contact creates challenges for model representation and control. For example, choosing and …
Beyond inverted pendulums: Task-optimal simple models of legged locomotion
Reduced-order models (ROMs) are popular in online motion planning due to their simplicity.
A good ROM for control captures critical task-relevant aspects of the full dynamics while …
A good ROM for control captures critical task-relevant aspects of the full dynamics while …
Reinforcement learning for reduced-order models of legged robots
Model-based approaches for planning and control for bipedal locomotion have a long
history of success. It can provide stability and safety guarantees while being effective in …
history of success. It can provide stability and safety guarantees while being effective in …
H2- and H∞-Optimal Model Predictive Controllers for Robust Legged Locomotion
This paper formally develops robust optimal predictive control solutions that can
accommodate disturbances and stabilize periodic legged locomotion. To this end, we build …
accommodate disturbances and stabilize periodic legged locomotion. To this end, we build …
Adaptive complexity model predictive control
This work introduces a formulation of model predictive control (MPC), which adaptively
reasons about the complexity of the model while maintaining feasibility and stability …
reasons about the complexity of the model while maintaining feasibility and stability …