5 papers
Beyond Bayesian Nash: Learning Minimax-Regret Equilibria for Adversarial Team Games under Asymmetric Information
Naman Aggarwal, Jonathan P. How
Adversarial team games (ATGs) with asymmetric information, such as adversarial path-finding, goal search, and reachability games on graphs, require strategies that are robust to hi…
Efficient Probabilistic Planning with Maximum-Coverage Distributionally Robust Backward Reachable Trees
Alex Rose, Naman Aggarwal, Christopher Jewison +1
This paper presents a new multi-query motion planning algorithm for linear Gaussian systems with the goal of reaching a Euclidean ball with high probability. We develop a new formu…
REVISE: Robust Probabilistic Motion Planning in a Gaussian Random Field
Alex Rose, Naman Aggarwal, Christopher Jewison +1
This paper presents Robust samplE-based coVarIance StEering (REVISE), a multi-query algorithm that generates robust belief roadmaps for dynamic systems navigating through spatially…
SDP Synthesis of Distributionally Robust Backward Reachable Trees for Probabilistic Planning
Naman Aggarwal, Jonathan P. How
The paper presents Maximal Ellipsoid Backward Reachable Trees MAXELLIPSOID BRT, which is a multi-query algorithm for planning of dynamic systems under stochastic motion uncertainty…
SDP Synthesis of Maximum Coverage Trees for Probabilistic Planning under Control Constraints
Naman Aggarwal, Jonathan P. How
The paper presents Maximal Covariance Backward Reachable Trees (MAXCOVAR BRT), which is a multi-query algorithm for planning of dynamic systems under stochastic motion uncertainty…