Minghao Qiu | Search arXiv

arXiv2026

Whole-Body Elasto-Geometrical Calibration of Wheeled Humanoid Robots Using a Shared-Waist Dual-Chain Model

Wheeled humanoid robots carry both arms on one actuated waist, usually without torque sensors, so the accuracy of both end-effectors depends on a single waist model. After a first stage that estimates the tracker and target extrinsics, we identify the waist and both arms in one problem from the target positions on both flanges, measured by an optical tracker. The kinematic model is complete, with waist-base, parallel-axis, and branch parameters; arm compliances are driven by measured torques and waist compliances by gravity torques of the robot's mass model; and Gaussian priors with evidence-maximizing scales stabilize the estimate. Independent and sequential single-chain calibration are restrictions of this problem, and its waist information is the sum of the single-chain Schur complements. On two robots with different waists, each without and with a payload, calibration reduces the mean errors on held-out poses from 11.3-31.1 mm to 0.50-1.11 mm. For every training-set size from 20 poses to all, the method has 17-63% lower mean errors than adaptations of two published whole-body calibration methods, mainly through the waist compliance. Independent calibration yields two waist models; using either for both arms raises the other arm's error to up to 3.21 mm.

cs.RO↗

arXiv2026

Evaluating differential air quality impacts of prescribed fire and wildfire in the United States

Increasing wildfire activities in the United States have generated far-reaching effects on air pollution and human health. While prescribed fires are used as a preventive strategy to reduce wildfire risks, the health impacts of their smoke remain uncertain. Small-scale case studies indicate that prescribed fires generally produce lower pollutant emissions than uncontrolled wildfires, potentially benefiting air quality. However, the extent to which this translates into reduced population-level smoke exposure remains uncertain due to a lack of robust, large-scale quantitative evidence. Moreover, the factors driving differences in air quality impacts between prescribed fires and wildfires were underexplored. Using fire data in California, Florida, and Georgia (2006-2020) and a causal forest approach, we quantified and compared the impacts of prescribed fires and wildfires on air quality, assessed their differences in population-level smoke exposure, and identified key factors influencing their smoke exposure levels. On a per square-kilometer basis, prescribed fires resulted in over six times less population-level smoke exposure compared to wildfires. Additionally, prescribed fires were associated with lower smoke exposure in regions with higher relative humidity and precipitation. This work could enable the broad risk-benefit assessment to guide the judicious use of prescribed fires and optimize public health outcomes while mitigating wildfire threats.

stat.AP↗