This paper contributes a method designed to enable autonomous distributed 3D nuclear radiation field mapping. The algorithm uses a single radiation sensor and a sequence of spatially distributed and robotically acquired radiation measurements across a discretized 3D grid to derive a radiation gradient. The derived gradient is probabilistically propagated to unknown components of the map to further guide a curiosity-driven path planner by identifying the next most radiologically informative point given available information. To demonstrate the method, we develop a resilient micro flying robot capable of autonomous GPS-denied navigation that integrates a Thallium–doped Cesium Iodide (CsI(Tl)) scintillator and Silicon Photomultiplier (SiPm) combined with custom–built pulse counting circuitry. A set of experimental studies is presented inside an indoor facility within which actual radioactive uranium ore sources have been distributed.

This work presents the design and autonomous navigation policy of the Resilient Micro Flyer, a new type of collision-tolerant robot tailored to fly through extremely confined environments and manhole-sized tubes. The robot maintains a low weight (<500g) and implements a combined rigid-compliant design through the integration of elastic flaps around its stiff collision-tolerant frame. These passive flaps ensure compliant collisions, contact sensing and smooth navigation in contact with the environment. Focusing on resilient autonomy, capable of running on resource-constrained hardware, we demonstrate the beneficial role of compliant collisions for the reliability of the onboard visual-inertial odometry and propose a safe navigation policy that exploits both collision-avoidance using lightweight time-of-flight sensing and adaptive control in response to collisions. The robot further realizes an explicit manhole navigation mode that exploits the direct mechanical feedback provided by the flaps and a special navigation strategy to self-align inside manholes with non-straight geometry. Comprehensive experimental studies are presented to evaluate, both individually and as a whole, how resilience is achieved based on the robot design and its navigation scheme.

In this paper the problem of contact-based navigation path planning for aerial robots is considered with the goal of enabling the autonomous in-contact operation on surfaces that can be highly anomalous. Such a capacity can prove critical in inspection through contact missions, as well as when a flying robot is tasked to operate in very narrow environments rendering safe free-flight impossible. To achieve this objective, beyond sliding in contact, a new locomotion primitive is introduced, namely that of azimuth rotations perpendicular to the surface under consideration. This new navigation mode, called flying cartwheel mode, offers navigation resourcefulness and resilience when the system is tasked to move in contact with surfaces that are otherwise non-traversable. The designed path planning method exploits both navigation modalities and a traversability metric to decide when to switch from sliding to flying cartwheel mode, and overall provides cost-optimal trajectories for in-contact navigation. The proposed approach is verified both in simulation, as well as experimentally using a surface presenting complex anomalies. It is highlighted that the proposed method does not assume any specialized contact mechanism or a control law tailored to physical interaction tasks, and hence is applicable to almost any micro aerial vehicle integrating protective shrouds around its propellers.

This paper details the system and methods designed to enable the autonomous estimation of distributed nuclear radiation fields within complex and possibly GPS-denied environments. A sensing apparatus consisting of three radially placed Thallium-doped Cesium Iodide (CsI(Tl)) scintillators and Silicon Photomultipliers (SiPm) combined with custom- built pulse counting circuitry is designed and the provided readings are pose-annotated using LiDAR-based localization. Given this capacity, a method that utilizes the radiation intensity readings to first calculate the immediate field gradient and then combine this information to update and co-estimate the believed field intensity and gradient across the whole environment is developed. The strategy propagates the effect of each local measurement through field gradient co-estimation and simultaneously derives a model of the underlying uncertainty. To further support the need for informative data gathering, especially in the framework of emergency and rapid reconnaissance missions, a path planning strategy is also developed that first utilizes the field intensity and uncertainty estimates to select its new waypoint and then performs terrain traversability analysis to derive admissible paths. The complete system is evaluated both in simulation and experimentally. The experimental results refer to the autonomous exploration and field estimation inside an indoor facility within which actual radioactive uranium and thorium ore sources have been distributed.

This paper presents a novel strategy for autonomous graph-based exploration path planning in subterranean environments. Attuned to the fact that subterranean settings, such as underground mines, are often large-scale networks of narrow tunnel-like and multi-branched topologies, the proposed planner is structured around a bifurcated local-and global-planner architecture. The local planner employs a rapidly-exploring random graph to reliably and efficiently identify collision-free paths that optimize an exploration gain within a local subspace. Accounting for the robot endurance limitations and the possibility that the local planner reaches a dead-end (e.g. a mine heading), the global planner is engaged when a return-to-home path must be derived or when the robot should be re-positioned towards an edge of the exploration space. The proposed planner is field evaluated in a collection of deployments inside both active and abandoned underground mines in the U.S. and in Switzerland.

This paper details the system and methods developed to enable autonomous nuclear radiation source localization and mapping using aerial robots in GPS-denied environments. A Thallium-doped Cesium Iodide (CsI(Tl)) scintillator and a Silicon Photomultiplier are combined with custom-built electronics for counting and spectroscopy, and the provided radiation measurements are pose-annotated using visual-inertial localization enabling autonomous operation in GPS-denied environments. Provided this capability, a strategy for radioactive source localization, as well as active source search path planning was developed. The proposed method is motivated and accounts for the limited endurance of the vehicle, which entails a very small amount of dwell points, and the fact that GPS-denied localization implies varying uncertainty of the robot's position estimate. The complete system is evaluated in multiple experimental studies using a small aerial robot and a Cesium-137 radiation source. As shown, accurate radioactive source localization is achieved, enabling efficient radiation mapping of indoor GPS-denied environments.