3 accepted papers
Visual Autoregressive (VAR) models enhance generation speed but face a critical efficiency bottleneck in later stages. In this paper, we present a novel optimization framework for VAR models that fundamentally differs from prior approaches such as FastVAR and SkipVAR. Instead of relying on heuristic…
Drawing inspiration from Maslow's “hierarchy of needs”, this paper develops a real-time control synthesis framework for robots to address hierarchical, complex objectives, recognizing that their behaviors are inherently driven by underlying needs. Each need is encoded by the zero-superlevel set of a
A coverage-based collaborative control strategy is developed in this paper for a multi-robot system with heterogeneous effective sensing ranges and safe operation zones to simultaneously estimate the states of and follow multiple targets governed by stochastic dynamics. Multiplicatively weighted Vor…