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Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM
Yipu Zhao, Justin S. Smith, Patricio A. Vela
The cost-efficiency of visual(-inertial) SLAM (VSLAM) is a critical characteristic of resource-limited applications. While hardware and algorithm advances have been significantly i…
Synthesis of Control Barrier Functions Using a Supervised Machine Learning Approach
Mohit Srinivasan, Amogh Dabholkar, Samuel Coogan +1
Control barrier functions are mathematical constructs used to guarantee safety for robotic systems. When integrated as constraints in a quadratic programming optimization problem,…
Closed-Loop Benchmarking of Stereo Visual-Inertial SLAM Systems: Understanding the Impact of Drift and Latency on Tracking Accuracy
Yipu Zhao, Justin S. Smith, Sambhu H. Karumanchi +1
Visual-inertial SLAM is essential for robot navigation in GPS-denied environments, e.g. indoor, underground. Conventionally, the performance of visual-inertial SLAM is evaluated wi…
Good Feature Matching: Towards Accurate, Robust VO/VSLAM with Low Latency
Yipu Zhao, Patricio A. Vela
Analysis of state-of-the-art VO/VSLAM system exposes a gap in balancing performance (accuracy & robustness) and efficiency (latency). Feature-based systems exhibit good performance…