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This paper introduces StarlETH, a compliant quadrupedal robot that is designed to study fast, efficient, and versatile locomotion. The platform is fully actuated with high compliant series elastic actuation, making the system torque controllable and at the same time well suited for highly dynamic maneuvers. We additionally emphasize key elements of a(More)
—This paper introduces a state estimation framework for legged robots that allows estimating the full pose of the robot without making any assumptions about the geometrical structure of its environment. This is achieved by means of an Observability Constrained Extended Kalman Filter that fuses kinematic encoder data with on-board IMU measurements. By(More)
Quadrupedal animals move through their environments with unmatched agility and grace. An important part of this is the ability to choose between different gaits in order to travel optimally at a certain speed or to robustly deal with unanticipated perturbations. In this paper, we present a control framework for a quadrupedal robot that is capable of(More)
—This paper introduces the concept of hybrid operational space control, a method that unifies kinematic tracking of individual joints with an inverse dynamics task space controller for the remainder of the robot. The proposed control strategy allows for a hierarchical task decomposition while simultaneously regulating the inner forces between the contact(More)
This paper presents the application of operational space control based on hierarchical task optimization for quadrupedal locomotion. We show how the behavior of a complex robotic machine can be described by a simple set of least squares problems with different priorities for motion, torque, and force optimization. Using projected dynamics of floating base(More)
This paper presents a state estimation approach for legged robots based on stochastic filtering. The key idea is to extract information from the kinematic constraints given through the intermittent contacts with the ground and to fuse this information with inertial measurements. To this end, we design an unscented Kalman filter based on a consistent(More)
This paper addresses the problem of evaluating and estimating the mechanical robustness of footholds for legged robots in unstructured terrain. In contrast to approaches that rely on human expert knowledge or human defined criteria to identify appropriate footholds, our method uses the robot itself to assess whether a certain foothold is adequate or not. To(More)
This article approaches the problem of controlling quadrupedal running and jumping motions with a parameterized, model-based, state-feedback controller. Inspired by the motor learning principles observed in nature, our method automatically fine tunes the parameters of our controller by repeatedly executing slight variations of the same motion task. This(More)
1 Motivation Legged locomotion enables humans and animals to traverse difficult terrain with great agility. Their skills to overcome large obstacles are impressive and superior to those of state-of-the-art legged robots. Our motivation is therefore to develop novel control methods for quadrupedal robots to increase their performance in this regard. More(More)