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Safely: Safe Stochastic Motion Planning Under Constrained Sensing via Duality
We introduce the Safely motion planner, a receding-horizon control framework, that simultaneously synthesizes both a trajectory for the robot to follow as well as a sensor selection strategy that prescribes trajectory-relevant obstacles to measure at each time step while respecting the sensing constraints of the robot.
Comparing Run Time Assurance Approaches for Safe Spacecraft Docking
Run Time Assurance (RTA) systems are online safety verification techniques that filter the output of a primary controller to assure safety.
Simultaneous Perception-Action Design via Invariant Finite Belief Sets
Although perception is an increasingly dominant portion of the overall computational cost for autonomous systems, only a fraction of the information perceived is likely to be relevant to the current task.
Point-Based Value Iteration and Approximately Optimal Dynamic Sensor Selection for Linear-Gaussian Processes
The problem of synthesizing an optimal sensor selection policy is pertinent to a variety of engineering applications ranging from event detection to autonomous navigation.
