8 accepted papers
In previous work, using a process we call meshing, the reachable state spaces for various continuous and hybrid systems were approximated as a discrete set of states which can then be synthesized into a Markov chain. One of the applications for this approach has been to analyze locomotion policies o…
Recent breakthroughs both in reinforcement learning and trajectory optimization have made significant advances towards real world robotic system deployment. Reinforcement learning (RL) can be applied to many problems without needing any modeling or intuition about the system, at the cost of high sam…
A key limitation in using various modern methods of machine learning in developing feedback control policies is the lack of appropriate methodologies to analyze their long-term dynamics, in terms of making any sort of guarantees (even statistically) about robustness. The central reasons for this are
Car models have been extensively studied at varying levels of abstraction, and planning and executing motions under ideal conditions is well researched and understood. For more aggressive maneuvers, for example when drifting or skidding, empirical and/or discontinuous friction models have been used…
Recent breakthroughs in the reinforcement learning (RL) community have made significant advances towards learning and deploying policies on real world robotic systems. However, even with current state-of-the-art algorithms and computational resources, these methods are still plagued with high sample…
This paper describes skating locomotion for a quadruped robot with dexterous limbs. The emphasis is on design of omnidirectional motion primitives and quantification of resulting speed and accuracy when traversing different types of smooth but potentially non-flat terrain. In particular, we study tr…
For an underactuated biped on a constant-slope terrain, the hybrid zero dynamics (HZD) controller framework provides exponentially stable walking motions. In this paper, we quantify the stability of such a control system on rough terrain by estimating the expected number of steps before failure. In…
This paper explores the use of a single passive design to stabilize frontal plane dynamics for 3D biped walking across a range of forward velocities and/or step lengths. Particular goals are to determine if design of sagittal plane control can be done independently from design of frontal plane stabi…