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Xia Hua

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2 papers

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IROS Conference 2025 Conference Paper

MobiExo: GPS-SLAM Fusion for Seamless Indoor-Outdoor Mobile Manipulation with Hand-Foot Coordination

Jianpeng Wang
Zhen Tian
Wenlong Chen
Dian Yuan
Zhou Zhou
Ming Cen
Xia Hua
Fei Yu

Teleoperation systems for mobile robots face significant challenges in achieving seamless coordination across dynamic environments. We present MobiExo, a teleoperation system that unlocks seamless indoor-outdoor mobile manipulation. Our approach tackles two fundamental challenges: robust cross-environment localization and intuitive full-body control. A novel self-adaptive federated filter unifies GPS and SLAM, delivering continuous centimeter-level positioning (4. 5±0. 8 cm indoor, 6. 8±1. 2 cm outdoor) and eliminating transition errors. Simultaneously, an integrated hand-foot coordination framework translates the operator’s natural gait and gestures into fluid robot actions, maintaining remarkable millimeter-level end-effector precision (3. 5±0. 4 mm) during navigation. Extensive field trials validate our design, demonstrating high task success (96. 7% indoor, 94. 3% outdoor) and a 5. 9× efficiency improvement in multi-location tasks over stationary setups. Code is available at: https://github.com/wangjianpeng200/MobiExo.git

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AAAI Conference 2012 Conference Paper

Optimal Proportional Cake Cutting with Connected Pieces

Xiaohui Bei
Ning Chen
Xia Hua
Biaoshuai Tao
Endong Yang

We consider the classic cake cutting problem where one allocates a divisible cake to n participating agents. Among all valid divisions, fairness and efficiency (a. k. a. social welfare) are the most critical criteria to satisfy and optimize, respectively. We study computational complexity of computing an efficiency optimal division given the conditions that the allocation satisfies proportional fairness and assigns each agent a connected piece. For linear valuation functions, we give a polynomial time approximation scheme to compute an efficiency optimal allocation. On the other hand, we show that the problem is NP-hard to approximate within a factor of Ω 1 √ n for general piecewise constant functions, and is NP-hard to compute for normalized functions.

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