Related papers: Estimating gravity acceleration from static atomic…
Long-term inertial navigation is currently limited by the bias drifts of gyroscopes and accelerometers and ultra-stable cold-atom interferometers offer a promising alternative for the next generation of high-end navigation systems. Here, we…
In high-precision atomic gravimeters, a rest mass is needed to provide a gravity reference, which is typically the retro-reflecting mirror of the Raman laser beams that addresses the two hyperfine ground states of the specific free-falling…
Gravity estimation is fundamental to visual-inertial perception, augmented reality, and robotics, yet gravity priors from IMUs are often unreliable under linear acceleration, vibration, and transient motion. Existing methods often estimate…
We present here a method for the extraction of the differential phase of an atom gradiometer that exploits the correlation of the vibration signal measured by an auxiliary classical sensor, such as a seismometer or an accelerometer. We show…
We focus on the fact that light-pulse atom interferometers measure the atoms' acceleration with only three data points per drop. As a result, the measured effect of the gravity gradient is systematically larger than the true one, an error…
This work proposes a resilient and adaptive state estimation framework for robots operating in perceptually-degraded environments. The approach, called Adaptive Maximum Correntropy Criterion Kalman Filtering (AMCCKF), is inherently robust…
We demonstrate a proof-of-principle of direct Earth gravity gradient measurement with an atom interferometer-based gravity gradiomter using a single proof mass of cold 87 rubidium atoms. The atomic gradiometer is implemented in the…
The Kalman filter (KF) provides optimal recursive state estimates for linear-Gaussian systems and underpins applications in control, signal processing, and others. However, it is vulnerable to outliers in the measurements and process noise.…
This paper is concerned with a problem of robust filtering for a finite-dimensional linear discrete time invariant system with two output signals, one of which is directly observed while the other has to be estimated. The system is assumed…
This work addresses the critical lack of precision in state estimation in the Kalman filter for 3D multi-object tracking (MOT) and the ongoing challenge of selecting the appropriate motion model. Existing literature commonly relies on…
Estimation of a dynamical system's latent state subject to sensor noise and model inaccuracies remains a critical yet difficult problem in robotics. While Kalman filters provide the optimal solution in the least squared sense for linear and…
Position-meter and speed-meter interferometers have been analysed for detecting gravitational waves. We introduce the concept of acceleration measurement in comparison with position and speed measurement. In this paper, we describe a…
In this paper we very preliminarily investigate the possibility of measuring the post-Newtonian general relativistic gravitoelectric and gravitomagnetic components of the acceleration of gravity on the Earth, in continuous regime, with two…
The precisions of existing gravitational calibrators for gravitational wave observatories are limited by their dependence on the relative position between the calibrators and the observatory's test masses. Here we present a novel geometry…
We discuss techniques for probing the effects of a constant force acting on cold atoms using two configurations of a grating echo-type atom interferometer. Laser-cooled samples of $^{85}$Rb with temperatures as low as 2.4 $\mu$K have been…
In this paper, we present a novel optimization algorithm designed specifically for estimating state-space models to deal with heavy-tailed measurement noise and constraints. Our algorithm addresses two significant limitations found in…
In this paper we are concerned with the error-covariance lower-bounding problem in Kalman filtering: a sensor releases a set of measurements to the data fusion/estimation center, which has a perfect knowledge of the dynamic model, to allow…
State estimation is crucial for legged robots as it directly affects control performance and locomotion stability. In this paper, we propose an Adaptive Invariant Extended Kalman Filter to improve proprioceptive state estimation for legged…
Rotor-based hopping locomotion significantly improves efficiency and operation time as compared to purely flying systems; where most hopping robots use the liftoff states and an assumed ballistic trajectory to determine the hopping height.…
Interferometric gravitational wave detectors operate by sensing the differential light travel time between free test masses. Correspondingly, they are sensitive to anything that changes the physical distance between the test masses,…