People who design, use, and are affected by autonomous artificially intelligent agents want
to be able to trust such agents—that is, to know that these agents will perform correctly, to …

Autonomous unmanned systems and robots must be able to actively leverage all available
information sources—including imprecise but readily available semantic observations …

This article develops novel strategies for optimal planning with semantic observations using
continuous state partially observable Markov decision processes (CPOMDPs). Two major …

Current methods of deploying robots that operate in dynamic, uncertain environments, such
as Uncrewed Aerial Systems in search & rescue missions, require nearly continuous human …

Deploying robots that operate in dynamic, uncertain environments, such as Uncrewed Aerial
Systems in search\& rescue missions, require nearly continuous human supervision for …

This note considers softmax parameter estimation when little/no labeled training data is
available, but a priori information about the relative geometry of class label log-odds …

In search applications, autonomous unmanned vehicles must be able to efficiently reacquire
and localize mobile targets that can remain out of view for long periods of time in large …

The ability of autonomous robots to model, communicate, and act on semantic “soft data”
remains challenging. The human-assisted robotic planning and sensing (HARPS) …

This work presents novel techniques for tightly integrated online information fusion and
planning in human-autonomy teams operating in partially known environments. Motivated …

Humans cannot always be treated as oracles for collaborative sensing. Robots, thus, need
to maintain beliefs over unknown world states when receiving semantic data from humans …