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Next generation space-based robotics systems will be constructed using distributed architectures where electronics capable of working in the extreme environments of the planets of the solar system are integrated with the sensors and actuators in plug-and-play modules and are connected through common multiple redundant data and power buses.
IAC system interactive tool for robotics design, integrating common database with programs from fields of structures, thermodynamics, controls and system dynamics. Written in FORTRAN 77.
The paper discusses the incorporation of vision into a robotic cell to obtain cell status information and use this information to influence the robot operation. It discusses both mechanical and informational solutions to the operational issues which are present. The cell uses a machine vision system to determine information about part presence in the shipping tray, part location in the tray, and tray orientation. The vision system's edge detector algorithm is used to identify the orientation of the packing trays. In addition, different vision tools are used to determine if parts are present in the trays based on the unique configuration of the individual parts. The mechanical solutions discuss the handling of medium weight (10 - 25 lb.) parts at an average cycle time of 3.1 seconds per part. The robot gripper must handle 33 different models, three identical parts at a time. This is accomplished by using stacks of rotary actuators and slides between the stacks.
An integration of 3-D vision systems with robot manipulators will allow robots to operate in a poorly structured environment by visually locating targets and obstacles. However, by using computer vision for objects acquisition makes the problem of overall system calibration even more difficult. Indeed, in a CAD based manipulation a control architecture has to find an accurate mapping between the 3-D Euclidean work space and a robot configuration space (joint angles). If a stereo vision is involved, then one needs to map a pair of 2-D video images directly into the robot configuration space. Neural Network approach aside, a common solution to this problem is to calibrate vision and manipulator independently, and then tie them via common mapping into the task space. In other words, both vision and robot refer to some common Absolute Euclidean Coordinate Frame via their individual mappings. This approach has two major difficulties. First a vision system has to be calibrated over the total work space. And second, the absolute frame, which is usually quite arbitrary, has to be the same with a high degree of precision for both robot and vision subsystem calibrations. The use of computer vision to allow robust fine motion manipulation in a poorly structured world which is currently in progress is described along with the preliminary results and encountered problems.
Existing Proportional-Integral-Derivative (PID) robotic controllers rely on an inverse kinematic model to convert user-specified cartesian trajectory coordinates to joint variables. These joints experience friction, stiction, and gear backlash effects. Due to lack of proper linearization of these effects, modern control theory based on state space methods cannot provide adequate control for robotic systems. In the presence of loads, the dynamic behavior of robotic systems is complex and nonlinear, especially where mathematical modeling is evaluated for real-time operators. Fuzzy Logic Control is a fast emerging alternative to conventional control systems in situations where it may not be feasible to formulate an analytical model of the complex system. Fuzzy logic techniques track a user-defined trajectory without having the host computer to explicitly solve the nonlinear inverse kinematic equations. The goal is to provide a rule-based approach, which is closer to human reasoning. The approach used expresses end-point error, location of manipulator joints, and proximity to obstacles as fuzzy variables. The resulting decisions are based upon linguistic and non-numerical information. This paper presents a solution to the conventional robot controller which is independent of computationally intensive kinematic equations. Computer simulation results of this approach as obtained from software implementation are also discussed.
We describe the design and analysis of an androgynous fastener for autonomous robotic assembly of high performance structures. The design of these fasteners aims to prioritize ease of assembly through simple actuation with large driver positioning tolerance requirements, while producing a reversible mechanical connection with high strength and stiffness per mass. This can be applied to high strength to weight ratio structural systems, such as discrete building block based systems that offer reconfigurability, scalability, and system lifecycle efficiency. Such periodic structures are suitable for navigation and manipulation by relatively small mobile robots. The integration of fasteners, which are lightweight and can be robotically installed, into a high performance robotically managed structural system is of interest to reduce launch energy requirements, enable higher mission adaptivity, and decrease system life-cycle costs.
In order for humans and robots to work effectively together, they need to be able to converse about abilities, goals and achievements. Thus, we are developing an interaction infrastructure called the "Human-Robot Interaction Operating System" (HRI/OS). The HRI/OS provides a structured software framework for building human-robot teams, supports a variety of user interfaces, enables humans and robots to engage in task-oriented dialogue, and facilitates integration of robots through an extensible API.
Planning will be an essential part of future autonomous robots and integrated intelligent systems. This paper focuses on learning problem solving knowledge in planning systems. The system is based on a common representation for macros, abstractions, and cases. Therefore, it is able to exploit both classical and case based techniques. The general operators in a successful plan derivation would be assessed for their potential usefulness, and some stored. The feasibility of this approach was studied through the implementation of a learning system for abstraction. New macros are motivated by trying to improve the operatorset. One heuristic used to improve the operator set is generating operators with more general preconditions than existing ones. This heuristic leads naturally to abstraction hierarchies. This investigation showed promising results on the towers of Hanoi problem. The paper concludes by describing methods for learning other problem solving knowledge. This knowledge can be represented by allowing operators at different levels of abstraction in a refinement.
Modeling high-precision in-space servicing, assembly, and manufacturing operations in a simulated environment is a critical step in the development of robotic systems that will be used to autonomously assemble large-scale structures in space. Limited facility size and high costs for manufacturing prototypes make it challenging to conduct full-scale operational testing under appropriate environmental conditions; therefore, testing in a modular, high-fidelity simulation environment is necessary for verification and validation of technology and architecture designs prior to launch. Several modeling and simulation environments exist both within NASA and industry that can be used to test robotic system design and operations, including the widely used commercial tool Gazebo integrated with Robotic Operating System software. Because the performance of autonomous robotic systems relies heavily on the quality of sensor input data, this paper focuses on assessing the accuracy of pose data from an optical sensor model in the Gazebo environment against the behavior of real hardware. The results of the tests will help developers using Gazebo for large-scale, high-precision simulation to account for modeling inaccuracies within their robotic control system algorithms.
This paper describes a comprehensive lunar exploration architecture developed by Marshall Space Flight Center's Advanced Concepts Office that features a science-based surface exploration strategy and a transportation architecture that uses two launches of a heavy lift launch vehicle to deliver human and robotic mission systems to the moon. The principal advantage of the dual launch lunar mission strategy is the reduced cost and risk resulting from the development of just one launch vehicle system. The dual launch lunar mission architecture may also enhance opportunities for commercial and international partnerships by using expendable launch vehicle services for robotic missions or development of surface exploration elements. Furthermore, this architecture is particularly suited to the integration of robotic and human exploration to maximize science return. For surface operations, an innovative dual-mode rover is presented that is capable of performing robotic science exploration as well as transporting human crew conducting surface exploration. The dual-mode rover can be deployed to the lunar surface to perform precursor science activities, collect samples, scout potential crew landing sites, and meet the crew at a designated landing site. With this approach, the crew is able to evaluate the robotically collected samples to select the best samples for return to Earth to maximize the scientific value. The rovers can continue robotic exploration after the crew leaves the lunar surface. The transportation system for the dual launch mission architecture uses a lunar-orbit-rendezvous strategy. Two heavy lift launch vehicles depart from Earth within a six hour period to transport the lunar lander and crew elements separately to lunar orbit. In lunar orbit, the crew transfer vehicle docks with the lander and the crew boards the lander for descent to the surface. After the surface mission, the crew returns to the orbiting transfer vehicle for the return to the Earth. This paper describes a complete transportation architecture including the analysis of transportation element options and sensitivities including: transportation element mass to surface landed mass; lander propellant options; and mission crew size. Based on this analysis, initial design concepts for the launch vehicle, crew module and lunar lander are presented. The paper also describes how the dual launch lunar mission architecture would fit into a more general overarching human space exploration philosophy that would allow expanded application of mission transportation elements for missions beyond the Earth-moon realm.
Crew time in space is precious – every hour could yield immense scientific discoveries and exploration milestones. However, overhead tasks such as logistics, maintenance, and assembly take a large portion of crew time. Remotely operated robotics capabilities offer a way to free the crew from many overhead tasks, but operating mobile dexterous robots in human-centered environments presents many unknowns and challenges for potential technology providers, limiting adoption for flight missions. iMETRO is a NASA JSC robotics test facility for terrestrial robotic technology adaptation to space exploration use cases, including logistics, maintenance, and science utilization. iMETRO focuses on Intra-Vehicular (IVA) environments, such as surface habitats, pressurized rover cabins, and space station modules (both Gateway & LEO). Its goal is to advance the Technology Readiness Levels (TRL) of integrated technologies for missions requiring remote space robotics operations.
The Space Suit RoboGlove is a device designed to provide additional grasp strength or endurance for an EVA crew member since gloved hand performance is a fraction of what the unencumbered human hand can achieve. There have been past efforts to approach this problem by employing novel materials and construction techniques to the glove design, as well as integrating powered assistance devices. This application of the NASA/GM RoboGlove technology uses a unique approach to integrate the robotic actuators and sensors into a Phase VI EVA glove. This design provides grasp augmentation to the glove user while active, but can also function as a normal glove when disabled. Care was taken to avoid adding excessive bulk to the glove or affecting tactility by choosing low-profile sensors and extrinsically locating the actuators. Conduits are used to guide robotic tendons from linear actuators, across the wrist, and to the fingers. The second generation of the SSRG includes updated electronics, sensors, and actuators to improve performance. The following discusses the electromechanical design, softgoods integration, and control system of the SSRG. It also presents test results from the first integration of a powered mobility element onto a space suit, the NASA Mark III. Early results show that sensor integration did not impact tactile feedback in the glove and the actuators show potential for reduction in grasp fatigue over time.
Dexterous manipulation of a robot hand requires the use of multiple sensors integrated into the mechanical hand under distributed microcomputer control. Where space applications such as construction, assembly, servicing and repair tasks are desired of smart robot arms and robot hands, several critical drives influence the design, engineering and integration of such an electromechanical hand. This paper describes a smart robot hand developed at the Jet Propulsion Laboratory for experimental use and evaluation with the Protoflight Manipulator Arm (PFMA) at the Marshall Space Flight Center (MSFC).
NASA employs Design Reference Missions (DRMs) to define potential architectures for future human exploration missions to deep space, the Moon, and Mars. While DRMs to these destinations share some components, each mission has different needs. This paper focuses on the human and automation/robotic integration needs for these future missions, evaluating them with respect to NASA research gaps in the area of space human factors engineering. The outcomes of our assessment is a human and automation/robotic (HAR) task list for each of the four DRMs that we reviewed (i.e., Deep Space Sortie, Lunar Visit/Habitation, Deep Space Habitation, and Planetary), a list of common critical HAR factors that drive HAR design.
NASA's Human Research Program (HRP) funds research efforts aimed at mitigating various human health and performance risks, including the Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI). As such, within HRP, the Human Factors and Behavioral Performance (HFBP) Element tasked an evaluation of future HARI needs in order to scope and focus the HARI risk research plan. The objective was to provide a systematic understanding of the critical factors associated with effective HARI that will be necessary to achieve the future mission goals for near- and deep-space exploration. Future mission goals are specified by NASA Design Reference Missions (DRMs) that are pertinent to the HRP. The outcome of this evaluation is a set of NASA-relevant HARI tasks, factors, and interactions required for exploration-class missions.
Introduction: Ablative heat shields are an enabling technology for entry into planetary atmospheres. From the PICA heatshields used for several Mars rovers to the carbon phenolic material used for Galileo’s Jupiter entry probe, the heat shield manages the heat load transferred to the payload, protecting the sensitive scientific instruments carried on entry probes. The Additive Manufacturing of Thermal Protection Systems (AMTPS) project, an Early Career Initiative (ECI) funded by NASA’s Space Technology Mission Directorate and led by NASA Johnson Space Center, seeks to develop materials and processes for 3D printing ablative heat shields for spacecraft. Current methods for producing ablative heat shields are extremely labor intensive and re-quire extensive hands-on processes and quality control characterization. Additive manufacturing (AM) offers the possibility of reduced production times, improved reliability, and enhanced performance via graded compositions. Costs will also be reduced by reducing the time and labor required for heat shield production. Direct integration of the heat shield onto the structure during processing simplifies integration and reduces risk. Material Development: A critical challenge for the project is development of a material system that can (1) be printed in a near-net shape process and (2) perform well as an ablator. Achieving printability requires the material to flow under applied pressure, but maintain its shape once extruded from the printer nozzle. Ablative performance is measured by a multitude of markers, including char yield, char strength, thermal conductivity, and recession rate. Furthermore, there are several mechanical and thermal property considerations for vehicle integration including coefficient of thermal expansion (CTE) and residual stress. AM technology will be leveraged to grade the material formulation and properties through the thickness of the heat shield, an architecture not possible with current manufacturing processes. To this end, “robust” material formulations have been pre-pared with higher density for use on the surface where most ablation will occur. “Insulative” material formulations, with lower density and lower thermal conductivity, are prepared for use in the depth of the heat shield. This graded architecture will re-duce the overall mass of the heat shield and reduce costs and/or increase scientific payload capacities. To achieve a material system with the required properties, multiple resins have been investigated in collaboration with NASA Ames Research Center. To tune printability and performance, resin additives were studied to improve flexibility of the cured material while maintaining acceptable ablative performance. Material coupons were printed and studied via a suite of mechanical and thermal characterization methods. Arc jet testing was conducted at NASA Ames Research Center to evaluate ablative performance and thermal protection under conditions expected in atmospheric entry. Manufacturing Scale-Up: A partnership with Oak Ridge National Laboratory (ORNL) aims to enable full-scale fabrication of a 3D printed heat shield. Leveraging expertise in manufacturing and 3D printing at ORNL, a mid-scale manufacturing demonstration unit will be built and tested, using a dual-layer ablative system printed directly onto the titanium structure. Work on robotic system integration is ongoing and efforts to scale up material mixing with a material compound will ensure accurate and homogenous composition. Flight Test: A hypersonic sub-orbital flight test will provide a rigorous test of material performance ranging from ablation, thermal management, and mechanical integrity. Design of the capsule has taken place in collaboration with the University of Kentucky. Data collected from the flight will inform future design efforts in material formulation, printing methodology, and heat shield-capsule integration.
The conference presents papers on segmentation techniques, three-dimensional recognition and representation, processing image sequences, and navigation and mobility. Particular attention is given to determining the pose of an object, adaptive least squares correlation with geometrical constraints, and the reliable formation of feature vectors for two-dimensional shape representation. Other topics include the real-time tracking of a target moving on a natural textured background, computer vision for the guidance of roving robots, and integrating sensory data for object recognition tasks.
Robot-joint motors integrated with control computer or computers. Robot controller uses only 1 microprocessor to control as many as 16 joint-actuating motors. Control system uses high-speed bus to communicate with joint-interface circuits, addressing scheme to write commands to several motors simultaneously, and efficient assembly-language servo code. Features enable control of 16 joints at 1-kHz servo rate. Suitable for control of motors in numerically-controlled manufacturing systems. Use of single joint-control processor results in few components, lower cost, and simpler architecture.