Collective behavior and task persistification in lazy and minimalist collectives

When individuals in a collective system are constrained in terms of sensing, memory, computation, or power reserves; the design of algorithms to control them becomes challenging. These individual limitations can be due to multiple reasons like the shrinking size of each agent for bulk manufacturing efficiency or enforced simplicity to attain cost efficiency. Whereas, in some areas like nano-medicine, the nature of the task itself warrants such simplicity. This thesis presents algorithms inspired by biological and statistical physics models to achieve useful collective behavior through simple local physical interactions and, minimalist approaches to persistify tasks for long durations in collectives with limited capabilities and energy reserves. The first part of the thesis presents a system of vibration-driven robots that embodies the features of simplicity described above. A combination of theory, experiment, and simulation is used to study dynamic aggregation behavior in these robots facilitated via short-range physical attraction potentials between agents. Collectives in a dynamically aggregated state are shown to be capable of transporting objects over relatively long distances in a finite arena. In the rest of the thesis, two different, yet complementary systems are studied and elaborated to highlight the usefulness of distributed inactivity and activity modulation in aiding persistification of tasks in collectives incapable of implementing complicated algorithms to incorporate regular energy replenishing cycles. To summarize, an approach to achieving dynamic aggregation and related tasks like object transport in a constrained brushbot system is described. Two different artificial and biological collective systems are explored to reveal strategies through which tasks can be persistified without requiring complicated computations, sensing, and memory.Ph.D

Long-duration robot autonomy: From control algorithms to robot design

The transition that robots are experiencing from controlled and often static working environments to unstructured and dynamic settings is unveiling the potential fragility of the design and control techniques employed to build and program them, respectively. A paramount of example of a discipline that, by construction, deals with robots operating under unknown and ever-changing conditions is long-duration robot autonomy. In fact, during long-term deployments, robots will find themselves in environmental scenarios which were not planned and accounted for during the design phase. These operating conditions offer a variety of challenges which are not encountered in any other discipline of robotics. This thesis presents control-theoretic techniques and mechanical design principles to be employed while conceiving, building, and programming robotic systems meant to remain operational over sustained amounts of time. Long-duration autonomy is studied and analyzed from two different, yet complementary, perspectives: control algorithms and robot design. In the context of the former, the persistification of robotic tasks is presented. This consists of an optimization-based control framework which allows robots to remain operational over time horizons that are much longer than the ones which would be allowed by the limited resources of energy with which they can ever be equipped. As regards the mechanical design aspect of long-duration robot autonomy, in the second part of this thesis, the SlothBot, a slow-paced solar-powered wire-traversing robot, is presented. This robot embodies the design principles required by an autonomous robotic system 1in order to remain functional for truly long periods of time, including energy efficiency, design simplicity, and fail-safeness. To conclude, the development of a robotic platform which stands at the intersection of design and control for long-duration autonomy is described. A class of vibration-driven robots, the brushbots, are analyzed both from a mechanical design perspective, and in terms of interaction control capabilities with the environment in which they are deployed.Ph.D

Distributed Coverage Hole Prevention for Visual Environmental Monitoring with Quadcopters via Nonsmooth Control Barrier Functions

This paper proposes a distributed coverage control strategy for quadcopters equipped with downward-facing cameras that prevents the appearance of unmonitored areas in between the quadcopters' fields of view (FOVs). We derive a necessary and sufficient condition for eliminating any unsurveilled area that may arise in between the FOVs among a trio of quadcopters by utilizing a power diagram, i.e. a weighted Voronoi diagram defined by radii of FOVs. Because this condition can be described as logically combined constraints, we leverage nonsmooth control barrier functions (NCBFs) to prevent the appearance of unmonitored areas among a team's FOV. We then investigate the symmetric properties of the proposed NCBFs to develop a distributed algorithm. The proposed algorithm can support the switching of the NCBFs caused by changes of the quadcopters composing trios. The existence of the control input satisfying NCBF conditions is analyzed by employing the characteristics of the power diagram. The proposed framework is synthesized with a coverage control law that maximizes the monitoring quality while reducing overlaps of FOVs. The proposed method is demonstrated in simulation and experiment.Comment: 17 pages, 18 figures, submitted to the IEEE Transactions on Robotic