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Towards Autonomous Inspection of Space Systems Using Mobile Robotic Sensor Platforms
The space transportation systems required to support NASA's Exploration Initiative will demand a high degree of reliability to ensure mission success. This reliability can be realized through autonomous fault/damage detection and repair capabilities. It is crucial that such capabilities are incorporated into these systems since it will be impractical to rely upon Extra-Vehicular Activity (EVA), visual inspection or tele-operation due to the costly, labor-intensive and time-consuming nature of these methods. One approach to achieving this capability is through the use of an autonomous inspection system comprised of miniature mobile sensor platforms that will cooperatively perform high confidence inspection of space vehicles and habitats. This paper will discuss the efforts to develop a small scale demonstration test-bed to investigate the feasibility of using autonomous mobile sensor platforms to perform inspection operations. Progress will be discussed in technology areas including: the hardware implementation and demonstration of robotic sensor platforms, the implementation of a hardware test-bed facility, and the investigation of collaborative control algorithms.
Control of free-flying space robot manipulator systems
New control techniques for self contained, autonomous free flying space robots were developed and tested experimentally. Free flying robots are envisioned as a key element of any successful long term presence in space. These robots must be capable of performing the assembly, maintenance, and inspection, and repair tasks that currently require human extravehicular activity (EVA). A set of research projects were developed and carried out using lab models of satellite robots and a flexible manipulator. The second generation space robot models use air cushion vehicle (ACV) technology to simulate in 2-D the drag free, zero g conditions of space. The current work is divided into 5 major projects: Global Navigation and Control of a Free Floating Robot, Cooperative Manipulation from a Free Flying Robot, Multiple Robot Cooperation, Thrusterless Robotic Locomotion, and Dynamic Payload Manipulation. These projects are examined in detail.
Navigating a Mobile Robot Across Terrain Using Fuzzy Logic
A strategy for autonomous navigation of a robotic vehicle across hazardous terrain involves the use of a measure of traversability of terrain within a fuzzy-logic conceptual framework. This navigation strategy requires no a priori information about the environment. Fuzzy logic was selected as a basic element of this strategy because it provides a formal methodology for representing and implementing a human driver s heuristic knowledge and operational experience. Within a fuzzy-logic framework, the attributes of human reasoning and decision- making can be formulated by simple IF (antecedent), THEN (consequent) rules coupled with easily understandable and natural linguistic representations. The linguistic values in the rule antecedents convey the imprecision associated with measurements taken by sensors onboard a mobile robot, while the linguistic values in the rule consequents represent the vagueness inherent in the reasoning processes to generate the control actions. The operational strategies of the human expert driver can be transferred, via fuzzy logic, to a robot-navigation strategy in the form of a set of simple conditional statements composed of linguistic variables. These linguistic variables are defined by fuzzy sets in accordance with user-defined membership functions. The main advantages of a fuzzy navigation strategy lie in the ability to extract heuristic rules from human experience and to obviate the need for an analytical model of the robot navigation process.
Task Description Language
Task Description Language (TDL) is an extension of the C++ programming language that enables programmers to quickly and easily write complex, concurrent computer programs for controlling real-time autonomous systems, including robots and spacecraft. TDL is based on earlier work (circa 1984 through 1989) on the Task Control Architecture (TCA). TDL provides syntactic support for hierarchical task-level control functions, including task decomposition, synchronization, execution monitoring, and exception handling. A Java-language-based compiler transforms TDL programs into pure C++ code that includes calls to a platform-independent task-control-management (TCM) library. TDL has been used to control and coordinate multiple heterogeneous robots in projects sponsored by NASA and the Defense Advanced Research Projects Agency (DARPA). It has also been used in Brazil to control an autonomous airship and in Canada to control a robotic manipulator.
WM26 Paper Multi-Robot Collaboration for Hazardous Environments
Hazardous nuclear and industrial facilities are rarely designed for robots. Work in these domains demand precise manipulation and robust mobility in cluttered, constrained spaces where off-the-shelf platforms struggle and “one-size-fits-all” machines become costly and complex. Idaho National Laboratory (INL) is developing an autonomous, multi-robot inspection system that coordinates task-specific platforms rather than relying on a single omni-tool robot. An electric truck serves as a power and compute hub for a custom manipulator co-developed with Florida International University (FIU), a commercial mini crawler, a pan–tilt–zoom camera, and a Nexxis Argus LiDAR mapping system. Working in concert, these robots generate spatial, radiation, and temperature maps of the pit environments at the Hanford Waste Tank Farms. These systems will capture visual records and environmental telemetry to allow for analysis post inspection. The system architecture uses Robot Operating System 2 (ROS 2) for publish/subscribe integration, NVIDIA Isaac Sim and Unity for simulation and visualization, and algorithms such as NVBlox to fuse data into unified 3D overlays. This robot-agnostic approach reduces operator burden by enabling autonomy across heterogeneous platforms and lets each robot be used where it is strongest. Having autonomous functions means operators don’t have to fully control multiple different components. The ease of use could allow for more widespread adoption of advanced robotics at waste management sites that see continued use. By coordinating simpler, purpose-built mechanisms, the approach lowers design and manufacturing complexity, reduces capital risk in contaminated settings, and improves controllability for complex inspection and manipulation tasks. We present the architecture, early results, and lessons learned from building and deploying this coordinated multi-robot system, with the goal of accelerating safe, cost-effective adoption of advanced robotics at waste-management sites.
Information Foraging and Change Detection for Automated Science Exploration
This paper presents a new algorithm for autonomous on-line exploration in unknown environments. The objective is to free remote scientists from possibly-infeasible extensive preliminary site investigation prior to sending robotic agents. We simulate a common exploration task for an autonomous robot sampling the environment at various locations and compare performance against simpler control strategies. An extension is proposed and evaluated that further permits operation in the presence of environmental variability in which the robot encounters a change in the distribution underlying sampling targets. Experimental results indicate a strong improvement in performance across varied parameter choices for the scenario.
Autonomous Evolution of Dynamic Gaits with Two Quadruped Robots
A challenging task that must be accomplished for every legged robot is creating the walking and running behaviors needed for it to move. In this paper we describe our system for autonomously evolving dynamic gaits on two of Sony's quadruped robots. Our evolutionary algorithm runs on board the robot and uses the robot's sensors to compute the quality of a gait without assistance from the experimenter. First we show the evolution of a pace and trot gait on the OPEN-R prototype robot. With the fastest gait, the robot moves at over 10/min/min., which is more than forty body-lengths/min. While these first gaits are somewhat sensitive to the robot and environment in which they are evolved, we then show the evolution of robust dynamic gaits, one of which is used on the ERS-110, the first consumer version of AIBO.
Experiments in Nonlinear Adaptive Control of Multi-Manipulator, Free-Flying Space Robots
Sophisticated robots can greatly enhance the role of humans in space by relieving astronauts of low level, tedious assembly and maintenance chores and allowing them to concentrate on higher level tasks. Robots and astronauts can work together efficiently, as a team; but the robot must be capable of accomplishing complex operations and yet be easy to use. Multiple cooperating manipulators are essential to dexterity and can broaden greatly the types of activities the robot can achieve; adding adaptive control can ease greatly robot usage by allowing the robot to change its own controller actions, without human intervention, in response to changes in its environment. Previous work in the Aerospace Robotics Laboratory (ARL) have shown the usefulness of a space robot with cooperating manipulators. The research presented in this dissertation extends that work by adding adaptive control. To help achieve this high level of robot sophistication, this research made several advances to the field of nonlinear adaptive control of robotic systems. A nonlinear adaptive control algorithm developed originally for control of robots, but requiring joint positions as inputs, was extended here to handle the much more general case of manipulator endpoint-position commands. A new system modelling technique, called system concatenation was developed to simplify the generation of a system model for complicated systems, such as a free-flying multiple-manipulator robot system. Finally, the task-space concept was introduced wherein the operator's inputs specify only the robot's task. The robot's subsequent autonomous performance of each task still involves, of course, endpoint positions and joint configurations as subsets. The combination of these developments resulted in a new adaptive control framework that is capable of continuously providing full adaptation capability to the complex space-robot system in all modes of operation. The new adaptive control algorithm easily handles free-flying systems with multiple, interacting manipulators, and extends naturally to even larger systems. The new adaptive controller was experimentally demonstrated on an ideal testbed in the ARL-A first-ever experimental model of a multi-manipulator, free-flying space robot that is capable of capturing and manipulating free-floating objects without requiring human assistance. A graphical user interface enhanced the robot usability: it enabled an operator situated at a remote location to issue high-level task description commands to the robot, and to monitor robot activities as it then carried out each assignment autonomously.
Needs for supervised space robots in space exploration
The areas of application for space robots in the Space Exploration Initiative (SEI) are examined by reviewing the roles of SEI supervised robots particularly with planet-surface systems (PSSs). Treatment is given to both teleoperated conventional robot systems and autonomous intelligent systems for comparison in terms of safety, reliability, and productivity. Two development stages are proposed including one with a robotic actor, human observer, and a human supervisor and a second in which a closed-loop control and monitoring system is established. The use of remote control is shown to require robustness, self-calibration and -diagnosis, adjustable autonomy, and multitask capability. The requirements of intelligent control are also listed so that the PSSs of the SEI can be used to enable surface exploration, local-resource utilization potential, and reductions of human tasks.
Quantifying Traversability of Terrain for a Mobile Robot
A document presents an updated discussion on a method of autonomous navigation for a robotic vehicle navigating across rough terrain. The method involves, among other things, the use of a measure of traversability, denoted the fuzzy traversability index, which embodies the information about the slope and roughness of terrain obtained from analysis of images acquired by cameras mounted on the robot. The improvements presented in the report focus on the use of the fuzzy traversability index to generate a traversability map and a grid map for planning the safest path for the robot. Once grid traversability values have been computed, they are utilized for rejecting unsafe path segments and for computing a traversalcost function for ranking candidate paths, selected by a search algorithm, from a specified initial position to a specified final position. The output of the algorithm is a set of waypoints designating a path having a minimal-traversal cost.
High fidelity ground deposition measurement with robots after explosive radiological dispersion
A team of scientists from the Remote Sensing Laboratory at Joint Base Andrews, Maryland, has assembled a remote-controlled robot to field a few sodium iodide scintillators of different size and shape 18″ above ground for measurement of ground deposition of gamma-emitting particles after an explosion of a radiological dispersal device. This system uses a high-precision differential GPS device with submeter accuracy for radiation mapping. The system is most useful in characterizing large-area contamination and detecting gamma radioactivity in invisible, submicron particulate debris deposited on the ground at surface level or embedded in subsurface up to 3″ deep. The system was assembled as part of a larger effort to integrate advanced radiological detection devices into autonomous or remote-controlled robotic systems to eliminate or minimize the need for emergency responders to enter areas that pose significant health and safety risks to humans following a major radiological incident or accident. Research into autonomous algorithms is required to develop automated robotic systems for radiological survey and characterization activities in highly contaminated areas. The scope of this project also includes developing communications pathways and supporting infrastructure capabilities for different types of robotic technologies. The expected result is an advanced autonomous robotic system with integrated radiation detection electronics that allows emergency response personnel to view data remotely and in real time for radiological emergency response and consequence management purposes.
Deep learning for electron and scanning probe microscopy: From materials design to atomic fabrication
Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with applications ranging from theory and materials prediction to high-throughput data analysis. In parallel, the recent successes in applying ML/AI methods for autonomous systems from robotics through self-driving cars to organic and inorganic synthesis are generating enthusiasm for the potential of these techniques to enable automated and autonomous experiment in imaging. Here, we discuss recent progress in application of machine learning methods in scanning transmission electron microscopy and scanning probe microscopy, from applications such as data compression and exploratory data analysis to physics learning to atomic fabrication.
Exploiting map plans as resources for action
When plans are used as programs for controlling the action of autonomous or teleoperated robots, their abstract representation can easily obscure a great deal of the critical knowledge that originally led to the planned course of action. An autonomous vehicle experiment is highlighted which illustrates how the information barriers created by abstraction can result in undesirable action. It is then shown how the same task can be performed correctly using plans as a resource for action. As a result of this simple change in outlook, problems requiring opportunistic reaction to unexpected changes in the environment can be solved.
High energy density picoliter-scale zinc-air microbatteries for colloidal robotics
The recent interest in microscopic autonomous systems, including microrobots, colloidal state machines, and smart dust, has created a need for microscale energy storage and harvesting. However, macroscopic materials for energy storage have noted incompatibilities with microfabrication techniques, creating substantial challenges to realizing microscale energy systems. Here, we photolithographically patterned a microscale zinc/platinum/SU-8 system to generate the highest energy density microbattery at the picoliter (10 −12 liter) scale. The device scavenges ambient or solution-dissolved oxygen for a zinc oxidation reaction, achieving an energy density ranging from 760 to 1070 watt-hours per liter at scales below 100 micrometers lateral and 2 micrometers thickness in size. The parallel nature of photolithography processes allows 10,000 devices per wafer to be released into solution as colloids with energy stored on board. Within a volume of only 2 picoliters each, these primary microbatteries can deliver open circuit voltages of 1.05 ± 0.12 volts, with total energies ranging from 5.5 ± 0.3 to 7.7 ± 1.0 microjoules and a maximum power near 2.7 nanowatts. We demonstrated that such systems can reliably power a micrometer-sized memristor circuit, providing access to nonvolatile memory. We also cycled power to drive the reversible bending of microscale bimorph actuators at 0.05 hertz for mechanical functions of colloidal robots. Additional capabilities, such as powering two distinct nanosensor types and a clock circuit, were also demonstrated. The high energy density, low volume, and simple configuration promise the mass fabrication and adoption of such picoliter zinc-air batteries for micrometer-scale, colloidal robotics with autonomous functions.
RoMPS concept review automatic control of space robot, volume 2
Topics related to robot operated materials processing in space (RoMPS) are presented in view graph form and include: (1) system concept; (2) Hitchhiker Interface Requirements; (3) robot axis control concepts; (4) Autonomous Experiment Management System; (5) Zymate Robot Controller; (6) Southwest SC-4 Computer; (7) oven control housekeeping data; and (8) power distribution.
An autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence
This paper describes a method for the design of autonomous spacecraft, based upon behavioral approaches to intelligent robotics. First, a number of previous spacecraft automation projects are reviewed. A methodology for the design of autonomous spacecraft is then presented, drawing upon both the European Space Agency technological center (ESTEC) automation and robotics methodology and the subsumption architecture for autonomous robots. A layered competency model for autonomous orbital spacecraft is proposed. A simple example of low level competencies and their interaction is presented in order to illustrate the methodology. Finally, the general principles adopted for the control hardware design of the AUSTRALIS-1 spacecraft are described. This system will provide an orbital experimental platform for spacecraft autonomy studies, supporting the exploration of different logical control models, different computational metaphors within the behavioral control framework, and different mappings from the logical control model to its physical implementation.
Test Results for Autonomous Assembly of Modular Space Structures
This paper presents test results for autonomous assembly of a modular space structure. A Universal Robots UR10e manipulator with a custom end-effector, known as the Grapple Tool, was used to join TriTruss structural modules. The TriTrusses and their assembly configuration were developed for an in-space assembled telescope conceptual design. The tests presented here were performed with a 1:2.8 dimensionally scaled version of the Tri-Trusses. Robot trajectories were generated autonomously using a sample-based motion planner and an a-priori worksite model. The test results verify the assembly concept of operations as well as the software requirements for the Grapple Tool. While the Grapple Tool used in the tests was designed for the 1:2.8 scale Tri-Trusses, it has the same actuators, software, and computation architecture as the version designed for the full scale structure. The test operations consist of picking up two TriTrusses from their stowed locations and joining them to a third TriTruss mounted on a test stand and joining them to each other. This constitutes the first three modules of the in-space assembled telescope conceptual design. The paper presents the robot behavioral architecture, the generated trajectories commanded, the actual trajectories of the robot, and actuator performance of the Grapple Tool.