6 papers · 1 filter
Sparse Variable Projection in Robotic Perception: Exploiting Separable Structure for Efficient Nonlinear Optimization
Alan Papalia, Nikolas Sanderson, Haoyu Han +3
Robotic perception often requires solving large nonlinear least-squares (NLS) problems. While sparsity has been well-exploited to scale solvers, a complementary and underexploited…
Practical and Performant Enhancements for Maximization of Algebraic Connectivity
Leonard Jung, Alan Papalia, Kevin Doherty +1
Long-term state estimation over graphs remains challenging as current graph estimation methods scale poorly on large, long-term graphs. To address this, our work advances a current…
Learning Smooth State-Dependent Traversability from Dense Point Clouds
Zihao Dong, Alan Papalia, Leonard Jung +4
A key open challenge in off-road autonomy is that the traversability of terrain often depends on the vehicle's state. In particular, some obstacles are only traversable from some o…
Verification of Visual Controllers via Compositional Geometric Transformations
Alexander Estornell, Leonard Jung, Michael Everett
Perception-based neural network controllers are increasingly used in autonomous systems that rely on visual inputs to operate in the real world. Ensuring the safety of such systems…
A Hybrid Framework for Efficient Koopman Operator Learning
Alexander Estornell, Leonard Jung, Alenna Spiro +2
Koopman analysis of a general dynamics system provides a linear Koopman operator and an embedded eigenfunction space, enabling the application of standard techniques from linear an…
Learning Verifiable Control Policies Using Relaxed Verification
Puja Chaudhury, Alexander Estornell, Michael Everett
To provide safety guarantees for learning-based control systems, recent work has developed formal verification methods to apply after training ends. However, if the trained policy…