Autonomous Mission-Driven Robots in Extreme Environments

Citation

Bouman, Amanda Rose (2022) Autonomous Mission-Driven Robots in Extreme Environments. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/a78d-kv42. https://resolver.caltech.edu/CaltechTHESIS:05172022-043237609

Abstract

Robotic autonomy systems that can negotiate harsh environments under time and communication constraints are critical to accomplishing many real-world missions. Such systems require an integrated software-hardware solution capable of robustly reasoning about a time-limited mission across a complex environment and negotiating extreme physical conditions during mission execution. To this end, I will discus the development of two field-tested systems designed for operation in GPS-denied areas: (i) a coverage planning framework that enables efficient exploration of large, unknown environments, and (ii) a ballistically-launched aircraft that converts to an autonomous, free-flying multirotor in order to provide rapid aerial surveillance.

The first system addresses the time-limited exploration problem by providing a planning strategy that seeks to maximize the area covered by a robot’s sensor footprint along a planned trajectory. In order to find solutions over large spatial extents (>1 km) and long temporal horizons (>1 hour), this coverage problem is decomposed into tractable subproblems by introducing spatial and temporal abstractions. Spatially, the robot-world belief is approximated by a task-dependent structure, enriched with environment map estimates. Temporally, the belief is approximated by the aggregation of multiple structures, each spanning a different spatial range. Cascaded uncertainty-aware solvers return a coverage plan over the stratified belief in real time. Coverage policies are constructed in a receding horizon fashion to ensure motion smoothness and resiliency to real-world stochasticity in perception and control. This coverage planning framework was extensively tested on physical robots in various real-world environments (caves, mines, subway systems, etc.) and served as the exploration strategy for a competing entry in the DARPA Subterranean Challenge.

The second system addresses rapid multirotor deployment for aerial data collection during emergencies. While multirotors are advantageous over fixed-winged systems due to their high maneuverability, their rotating blades are hazardous and require stable, uncluttered takeoff sites. To overcome this issue, a ballistically-launched, autonomously-stabilizing multirotor (SQUID -- Streamlined Quick Unfolding Investigation Drone) was designed, fabricated, and tested. SQUID follows a deterministic trajectory, transitioning from a folded launch configuration to an autonomous, fully-controllable hexacopter. The entire process from launch to position stabilization requires no user- or GPS-input and demonstrates the viability of using ballistically-launched multirotors to achieve safe and rapid deployment from moving vehicles.

Thesis Files