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Passive-dynamic walkers are simple mechanical devices, composed of solid parts connected by joints, that walk stably down a slope. They have no motors or controllers, yet can have remarkably humanlike motions. This suggests that these machines are useful models of human locomotion; however, they cannot walk on level ground. Here we present three robots(More)
We cast the partially observable control problem as a fully observable underactuated stochastic control problem in belief space and apply standard planning and control techniques. One of the difficulties of belief space planning is modeling the stochastic dynamics resulting from unknown future observations. The core of our proposal is to define(More)
We present a learning system which is able to quickly and reliably acquire a robust feedback control policy for 3D dynamic walking from a blank-slate using only trials implemented on our physical robot. The robot begins walking within a minute and learning converges in approximately 20 minutes. This success can be attributed to the mechanics of our robot,(More)
Kinodynamic planning algorithms like Rapidly-Exploring Randomized Trees (RRTs) hold the promise of finding feasible trajectories for rich dynamical systems with complex, nonconvex constraints. In practice, these algorithms perform very well on configuration space planning, but struggle to grow efficiently in systems with dynamics or differential(More)
Advances in the direct computation of Lyapunov functions using convex optimization make it possible to efficiently evaluate regions of attraction for smooth nonlinear systems. Here we present a feedback motion planning algorithm which uses rigorously computed stability regions to build a sparse tree of LQR-stabilized trajectories. The region of attraction(More)
Legged robots that operate in the real world are inherently subject to stochasticity in their dynamics and uncertainty about the terrain. Due to limited energy budgets and limited control authority, these “disturbances” cannot always be canceled out with high-gain feedback. Minimally-actuated walking machines subject to stochastic disturbances no longer(More)
High-precision maneuvers at high angles-of-attack are not properly addressed by even the most advanced aircraft control systems. Here we present our control design procedure and indoor experimental results with a small fixed-wing autonomous glider which is capable of executing an aggressive high angle-of-attack maneuver in order to land on a perch. We first(More)
The passive dynamic walker described in this paper is a robot with a minimal number of degrees of freedom which is still capable of stable 3D dynamic walking. First, we present the reduced-order dynamic models used to tune the characteristics of the robot's passive gait. Our sagittal plane model is closely related to the compass gait model, but the steady(More)