Robotic agents can continuously provide feedback to people based on their behaviors. For instance, a robot swarm can remind a group of people to respect social distancing guidelines during a pandemic or discourage unwanted behavior such as littering. However, developing a swarm robot to operate in realistic situations is challenging: a robot requires significant resources to operate in the real world, yet costs need to be kept low to produce the robots en masse.
To develop a swarm robot for encouraging social distancing, we therefore, compare the performance of different robotic navigation algorithms and various vision sensors and algorithms for detecting social distances breaches.

The Internet of Things (IoT) is expected to include billions of tiny devices that collect, process, and communicate sensory data. As of now, batteries power these devices. Batteries, however, are large, expensive, and short-lived - even the rechargeable ones wear out in a few years. Therefore, they are not a sustainable powering solution. Tiny battery-less devices promise a maintenance-free and environment-friendly alternative. They operate by harvesting energy from the environment. Ambient power, however, is marginal and unpredictable. This causes tiny energy-harvesting devices to operate intermittently, violating the requirements of many real-world applications.
This work presents an event-based command-recognition algorithm tailored towards battery-less sensors, taking into account the challenges of intermittent execution and the ultra-low-power hardware. Our algorithm achieves a 97% recognition accuracy with a ten-word vocabulary.

Progress has been made recently in the research of equal hierarchy backscatter communications. There are, however, challenges to overcome before this technology can become mainstream. For example, state-of-the-art solutions to the phase cancellation problem that occurs in such networks are still trivial and sub-optimal, especially in terms of resource utilization. This thesis aims to address the issue by designing a novel networking algorithm. This is done by (i) characterizing and analyzing such networks to assess the potential of the proposal, and (ii) experimentally demonstrating the concept in the largest implemented network so far. Findings show that the solution presented in this work not only matches current phase cancellation solutions in terms of robustness, but also extends communication range and enables connecting networks served by separate exciters.