The New Bottom Line: Black Women Cultural Entrepreneurs Re-Define Success in The Connected Economy

Black women cultural entrepreneurs are a group of entrepreneurs that merit further inquiry. Using qualitative interview and participant observation data, this dissertation investigates the ways in which black women cultural entrepreneurs define success. My findings reveal that black women cultural entrepreneurs are a particular interpretive community with values, perspectives and experiences, which are not wholly idiosyncratic, but shaped by collective experiences and larger social forces. Black women are not a monolith, but they are neither disconnected individuals completely devoid of group identity. The meaning they give to their businesses, professional experiences and understandings of success are influenced by their shared social position and identity as black women. For black women cultural entrepreneurs, the New Bottom Line goes beyond financial gain. This group, while not uniform in their understandings of success, largely understand the most meaningful accomplishments they can realize as social impact in the form of cultural intervention, black community uplift and professional/creative agency. These particular considerations represent a new paramount concern, and alternative understanding of what is typically understood as the bottom line. The structural, social and personal challenges that black women cultural entrepreneurs encounter have shaped their particular perspectives on success. I also explore the ways research participants articulated an oppositional consciousness to create an alternative means of defining and achieving success. I argue that this consciousness empowers them with resources, connections and meaning not readily conferred in traditional entrepreneurial settings. In this sense, the personal, social and structural challenges have been foundational to the formation of an alternative economy, which I refer to as The Connected Economy. Leading and participating in The Connected Economy, black women cultural entrepreneurs represent a black feminist and womanist critique of dominant understandings of success.

Motion Planning and Controls with Safety and Temporal Constraints

Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.