Barath Raghavan

Heramb Nemlekar, Ziang Liu, Suraj Kothawade et al.

The problem of robotic lime picking is challenging; lime plants have dense foliage which makes it difficult for a robotic arm to grasp a lime without coming in contact with leaves. Existing approaches either do not consider leaves, or treat them as obstacles and completely avoid them, often resulting in undesirable or infeasible plans. We focus on reaching a lime in the presence of dense foliage by considering the leaves of a plant as 'permeable obstacles' with a collision cost. We then adapt the rapidly exploring random tree star (RRT*) algorithm for the problem of fruit harvesting by incorporating the cost of collision with leaves into the path cost. To reduce the time required for finding low-cost paths to goal, we bias the growth of the tree using an artificial potential field (APF). We compare our proposed method with prior work in a 2-D environment and a 6-DOF robot simulation. Our experiments and a real-world demonstration on a robotic lime picking task demonstrate the applicability of our approach.

Sarah Cooney, Barath Raghavan

The process of revitalizing cities in the United States suffers from balky and unresponsive processes---de jure egalitarian but de facto controlled and mediated by city officials and powerful interests, not residents. We argue that, instead, our goal should be to put city planning in the hands of the people, and to that end, give ordinary residents pattern-based planning tools to help them redesign (and repair) their urban surrounds. Through this, residents can explore many disparate ideas, try them, and, if successful, replicate them, enabling bottom-up city planning through direct action. We describe a prototype for such a tool that leverages classic patterns to enable city planning by residents, using case studies from Los Angeles as guides for both the problem and potential solution.

Adam Lerner, Giulia Fanti, Yahel Ben-David et al.

In recent years governments have shown themselves willing to impose blackouts to shut off key communication infrastructure during times of civil strife, and to surveil citizen communications whenever possible. However, it is exactly during such strife that citizens need reliable and anonymous communications the most. In this paper, we present Rangzen, a system for anonymous broadcast messaging during network blackouts. Rangzen is distinctive in both aim and design. Our aim is to provide an anonymous, one-to-many messaging layer that requires only users' smartphones and can withstand network-level attacks. Our design is a delay-tolerant mesh network which deprioritizes adversarial messages by means of a social graph while preserving user anonymity. We built a complete implementation that runs on Android smartphones, present benchmarks of its performance and battery usage, and present simulation results suggesting Rangzen's efficacy at scale.