Aaron Morris

A robotic walker that provides guidance

This paper describes a robotic walker designed as an assistive device for frail elderly people with cognitive impairment. Locomotion is most often the primary form of exercise for the elderly, and devices that provide mobility assistance are critical for the health and well being of such individuals. Previous work on walkers focused primarily on safety but offered little or no assistance with navigation and global orientation. Our system provides these features in addition to the stability and support provided by conventional walkers. A software suite of robot localization and navigation combined with a shared-control haptic interface achieves this capability. The system has been tested in a retirement facility near Pittsburgh, PA, USA.

A campaign in autonomous mine mapping

Unknown, unexplored and abandoned subterranean voids threaten mining operations, surface developments and the environment. Hazards within these spaces preclude human access to create and verify extensive maps or to characterize and analyze the environment. To that end, we have developed a mobile robot capable of autonomously exploring and mapping abandoned mines. To operate without communications in a harsh environment with little chance of rescue, this robot must have a robust electro-mechanical platform, a reliable software system, and a dependable means of failure recovery. Presented are the mechanisms, algorithms, and analysis tools that enable autonomous mine exploration and mapping along with extensive experimental results from eight successful deployments into the abandoned Mathies coal mine near Pittsburgh, PA.

Recent developments in subterranean robotics

Robotic systems exhibit remarkable capability for exploring and mapping subterranean voids. Information about subterranean spaces has immense value for civil, security, and commercial applications where problems, such as encroachment, collapse, flooding and subsidence can occur. Contemporary method for underground mapping, such as human surveys and geophysical techniques, can provide estimates of void location, but cannot achieve the coverage, quality, or economy of robotic approaches. This article presents the challenges, mechanisms, sensing, and software of subterranean robots. Results obtained from operations in active, abandoned, and submerged subterranean spaces will also be shown.

Towards Topological Exploration of Abandoned Mines

The need for reliable maps of subterranean spaces too hazardous for humans to occupy has motivated the use of robotic technology as mapping tools. As such, we present a systemic approach to autonomous topological exploration of a mine environment to facilitate the process of mapping. This approach focuses upon the interaction of three high-level processes: topological planning, intersection identification and local navigation. Topological planning tasks the robot to investigate stretches of mine corridor for the purpose of collecting data. Intersection identification converts sensory input into topological components used to construct an online topological map and provide the robot with a global sense of position. Local navigation transforms topological exploration objectives into robot actuation enabling traversal of mine corridors. These processes are described in detail with results presented from experiments conducted at a research coal mine near Pittsburgh, PA.

Comparative evaluation of range sensing technologies for underground void modeling

This paper compares a broad cross-section of range sensing technologies for underground void modeling. In this family of applications, a tunnel environment is incrementally mapped with range sensors from a mobile robot to recover scene geometry. Distinguishing contributions of this work include an unprecedented number of configurations evaluated utilizing common methodology and metrics as well as a significant in situ environmental component lacking in prior characterization work. Sensors are experimentally compared against both an ideal geometric target and in example void environments such as a mine and underground tunnel. Three natural groupings of sensors were identified from these results and performances were found to be strongly cost-correlated. While the results presented are specific to the experimental configurations tested, the generality of tunnel environments and the metrics of reconstruction are extensible to a spectrum of outdoor and surface applications.

Topological exploration of subterranean environments

The need for reliable maps of subterranean spaces too hazardous for humans to occupy has motivated the development of robotic mapping tools suited to these domains. As such, this work describes a system developed for autonomous topological exploration of mine environments to facilitate the process of mapping. The exploration framework is based upon the interaction of three main components: Node detection, node matching, and edge exploration. Node detection robustly identifies mine corridor intersections from sensor data and uses these features as the building blocks of a topological map. Node matching compares newly observed intersections to those stored in the map, providing global localization during exploration. Edge exploration translates topological exploration objectives into locomotion along mine corridors. This article describes both the robotic platform and the algorithms developed for exploration, and presents results from experiments conducted at a research coal mine near Pittsburgh, PA.

Feature extraction for topological mine maps

We present a robust method for detecting and recognizing topological features in underground mines. Our method involves performing Delaunay triangulations on range scans to extract points of interest, such as intersecting corridors. By combining these interest points into a topological map, we have a valuable tool for navigation and localization in large scale, highly cyclic environments. We present results from a research coal mine near Pittsburgh, PA.

Adaptive Multi-Robot, Multi-Operator Work Systems

Unstructured and hostile environments impose great risk to exposed humans and present ideal domains for robotic forces; however, these dynamic environments pose considerable difficulty in autonomous multi-robot coordination, making a need for supervisory control paramount. This paper examines a three-phase approach that increases the robustness, reliability, and efficiency of human-machine work systems by dynamically altering the soldier-robot control relationships as well as the effective autonomy manifested by each robot function in response to estimated cognitive loading (stress). This approach enables an adaptive command and control structure across a spectrum of force configurations.

The Process Information Space: The Importance of Data Flow in Robotic Systems

Data flow describes the motion of information through a robotic system. As this work investigates, data flow can also provide system-critical information about the robot that is useful for failure recognition, fault recovery and improved robot dependability. The approach developed in this paper applies a planning formulation to the observation and control of data flow through the reconfiguration of robot process connections. Simulated results are presented and a subterranean robot application is discussed

A Scalable Command and Control System for Human-Machine Work Systems

The emergence of complex work systems has yielded new challenges for efficient and reliable collaboration between humans and machines. Robots are now working autonomously beside human counterparts to accomplish critical tasks; however fully autonomous robot action is still considered unreliable. This paper examines an approach to increasing the robustness, reliability, and efficiency of human-machine work systems by dynamically establishing dynamic control relationships between humans and robots as well as altering the effective autonomy manifested by each robot. The process involves workload estimation to determine the parameters of the system, workload optimization to analyze and modify system parameters, and workload mitigation to enact these modifications in a non-intrusive manner. Furthermore, heuristic approaches to approximating an optimal system configuration for real-time environments are also addressed and simulated.