Visual body signals are designated body poses that deliver an application-specific message. Such signals are widely used for fast message communication in sports (signaling by umpires and referees), transportation (naval officers and aircraft marshallers), and construction (signaling by riggers and crane operators), to list a few examples. Automatic interpretation of such signals can help maintaining safer operations in these industries, help in record-keeping for auditing or accident investigation purposes, and function as a score-keeper in sports. When automation of these signals is desired, it is traditionally performed from a viewer's perspective by running computer vision algorithms on camera feeds. However, computer vision based approaches suffer from performance deterioration in scenarios such as lighting variations, occlusions, etc., might face resolution limitations, and can be challenging to install. Our work, ViSig, breaks with tradition by instead deploying on-body sensors for signal interpretation. Our key innovation is the fusion of ultra-wideband (UWB) sensors for capturing on-body distance measurements, inertial sensors (IMU) for capturing orientation of a few body segments, and photodiodes for finger signal recognition, enabling a robust interpretation of signals. By deploying only a small number of sensors, we show that body signals can be interpreted unambiguously in many different settings, including in games of Cricket, Baseball, and Football, and in operational safety use-cases such as crane operations and flag semaphores for maritime navigation, with > 90% accuracy. Overall, we have seen substantial promise in this approach and expect a large body of future follow-on work to start using UWB and IMU fused modalities for the more general human pose estimation problems.
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Finite Horizon Maximum Likelihood Estimation for Integrated Navigation with RF Beacon Measurements
We develop a Finite Horizon Maximum Likelihood Estimator (FHMLE) that fuses Inertial Measurement Unit (IMU) and radio frequency (RF) measurements over a sliding window of finite length for three‐dimensional navigation. Available RF data includes pseudo–ranges, angles of transmission (AoT), and Doppler shift measurements. The navigation estimates are obtained by solving a finite‐dimensional nonlinear optimization using a primal‐dual interior point algorithm (PDIP). The benefits of the proposed estimation method are highlighted using simulations results comparing the FHMLE approach with an Unscented Kalman Filter (UKF), in a scenario where an aircraft approaches a carrier, with RF measurements from beacons aboard the carrier, and low‐cost IMU measurements aboard the aircraft. When the Geometric Dilution of Precision is large, we found that the FHMLE is able to achieve smaller estimation errors than the UKF, which tends to carry a bias throughout the trajectory.
more » « less- NSF-PAR ID:
- 10458660
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Asian Journal of Control
- Volume:
- 21
- Issue:
- 4
- ISSN:
- 1561-8625
- Page Range / eLocation ID:
- p. 1470-1482
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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