SpecificationBased Maneuvering of Quadcopters Through Hoops In this paper, we study the problem of navigating quadcopters through a sequence of hoops. The specification may be given directly or indirectly via a linear temporal logic (LTL) formula. We approach this problem in three phases. First, we introduce a planner that generates a path through a given sequence of hoops. Second, we augment our planner to leverage a given specification in linear temporal logic (LTL) and generate a sequence that satisfies this specification. Third, we implement crossentropy optimization on this planner to enhance trajectory performance where quadcopter trajectories are modified within the solution space to optimize over a cost function. We implement this planner as a novel interaction modality between users and quadcopters on the Robotarium. Simulation and experimental results are provided.

From Specifications to Behavior: Maneuver Verification in a Semantic State Space To realize a market entry of autonomous vehicles in the foreseeable future, the behavior planning system will need to abide by the same rules that humans follow. Product liability cannot be enforced without a proper solution to the approval trap. In this paper, we define a semantic abstraction of the continuous space and formalize traffic rules in linear temporal logic (LTL). Sequences in the semantic state space represent maneuvers a highlevel planner could choose to execute. We check these maneuvers against the formalized traffic rules using runtime verification. By using the standard model checker NuSMV, we demonstrate the effectiveness of our approach and provide runtime properties for the maneuver verification. We show that highlevel behavior can be verified in a semantic state space to fulfill a set of formalized rules, which could serve as a step towards safety of the intended functionality.