1 citations · 1 across the 6 of their papers we have counts for
6 papers
Bicycle Acrobatics with Reinforcement Learning
Shamel Fahmi, Arianna Ilvonen, Samuel Zapolsky +8
Bicycle robots are fast and energy efficient, but their simple mechanical design and their underactuated and non-holonomic dynamics make highly agile maneuvers difficult to achieve…
System Design of the Ultra Mobility Vehicle: A Driving, Balancing, and Jumping Bicycle Robot
Benjamin Bokser, Daniel Gonzalez, Aaron Preston +39
Trials cyclists and mountain bike riders can hop, jump, balance, and drive on one or both wheels. This versatility allows them to achieve speed and energy-efficiency on smooth terr…
Sparsity Inducing Representations for Policy Decompositions
Ashwin Khadke, Hartmut Geyer
Policy Decomposition (PoDec) is a framework that lessens the curse of dimensionality when deriving policies to optimal control problems. For a given system representation, i.e. the…
Search Methods for Policy Decompositions
Ashwin Khadke, Hartmut Geyer
Computing optimal control policies for complex dynamical systems requires approximation methods to remain computationally tractable. Several approximation methods have been develop…
Policy Decomposition: Approximate Optimal Control with Suboptimality Estimates
Ashwin Khadke, Hartmut Geyer
Numerically computing global policies to optimal control problems for complex dynamical systems is mostly intractable. In consequence, a number of approximation methods have been d…
What Can This Robot Do? Learning from Appearance and Experiments
Ashwin Khadke, Manuela Veloso
When presented with an unknown robot (subject) how can an autonomous agent (learner) figure out what this new robot can do? The subject's appearance can provide cues to its physica…