How to teach a van to drive: an undergraduate perspective on the 2005 DARPA Grand Challenge

This paper describes how a team of undergraduate volunteers from California Institute of Technology (Caltech) developed a robotic vehicle that can navigate completely autonomously through the Mojave Desert. Called Alice, the vehicle was Caltech's entry to the 2005 DARPA Grand Challenge which aimed to generate the technology needed to build and program an unmanned ground vehicle through 130 miles of difficult terrain completely autonomously in under ten hours. Although Alice failed to win the competition, she did succeed in her original purpose of teaching a new generation of students about engineering, how to apply theory to the real world, how to debug and deal with shortcomings and schedules, and most importantly, how to work as a team on a complex problem

Rocksprings

This paper won a second place writing flag award in the creative/reflective category. It was written for Lester Faigley's E 379R class, "Travel Literature".Faigley, LesterUndergraduate Studie

Qualitative Reachability for Open Interval Markov Chains

Interval Markov chains extend classical Markov chains with the possibility to describe transition probabilities using intervals, rather than exact values. While the standard formulation of interval Markov chains features closed intervals, previous work has considered also open interval Markov chains, in which the intervals can also be open or half-open. In this paper we focus on qualitative reachability problems for open interval Markov chains, which consider whether the optimal (maximum or minimum) probability with which a certain set of states can be reached is equal to 0 or 1. We present polynomial-time algorithms for these problems for both of the standard semantics of interval Markov chains. Our methods do not rely on the closure of open intervals, in contrast to previous approaches for open interval Markov chains, and can characterise situations in which probability 0 or 1 can be attained not exactly but arbitrarily closely.Comment: Full version of a paper published at RP 201