Engineering topics

Kortenkamp, David

Publications and source records attributed to Kortenkamp, David.

8 records

NASA NTRS2005

Using Dynamic Simulations and Automated Decision Tools to Design Lunar Habitats

This paper describes the role of transient simulations, heuristic techniques, and closed loop integrated control in designing and sizing habitat life support systems. The integration of these three elements allows for more accurate requirements to be derived in advance of hardware choices. As a test case, we used a typical lunar surface habitat. Large numbers of habitat configurations were rapidly tested and evaluated using automated decision support tools. Through this process, preliminary sizing for habitat life support systems were derived. Our preliminary results show that by using transient simulations and closed loop control , we substantially reduced the system mass required to meet mission goals. This has greater implications for general systems analyses and for life support systems. It is likely that transient models, realtime integrated control, and other analyses capable of capturing the uncertainties of systems can be useful for systems analyses much earlier in the system development life cycle than has previously been considered.

Bell, Scott↗

NASA NTRS2005

Trusted Autonomy for Space Flight Systems

NASA has long supported research on intelligent control technologies that could allow space systems to operate autonomously or with reduced human supervision. Proposed uses range from automated control of entire space vehicles to mobile robots that assist or substitute for astronauts to vehicle systems such as life support that interact with other systems in complex ways and require constant vigilance. The potential for pervasive use of such technology to extend the kinds of missions that are possible in practice is well understood, as is its potential to radically improve the robustness, safety and productivity of diverse mission systems. Despite its acknowledged potential, intelligent control capabilities are rarely used in space flight systems. Perhaps the most famous example of intelligent control on a spacecraft is the Remote Agent system flown on the Deep Space One mission (1998 - 2001). However, even in this case, the role of the intelligent control element, originally intended to have full control of the spacecraft for the duration of the mission, was reduced to having partial control for a two-week non-critical period. Even this level of mission acceptance was exceptional. In most cases, mission managers consider intelligent control systems an unacceptable source of risk and elect not to fly them. Overall, the technology is not trusted. From the standpoint of those who need to decide whether to incorporate this technology, lack of trust is easy to understand. Intelligent high-level control means allowing software io make decisions that are too complex for conventional software. The decision-making behavior of these systems is often hard to understand and inspect, and thus hard to evaluate. Moreover, such software is typically designed and implemented either as a research product or custom-built for a particular mission. In the former case, software quality is unlikely to be adequate for flight qualification and the functionality provided by the system is likely driven largely by the need to publish innovative work. In the latter case, the mission represents the first use of the system, a risky proposition even for relatively simple software.

Freed, Michael↗

NASA NTRS2005

Planner-Based Control of Advanced Life Support Systems

The paper describes an approach to the integration of qualitative and quantitative modeling techniques for advanced life support (ALS) systems. Developing reliable control strategies that scale up to fully integrated life support systems requires augmenting quantitative models and control algorithms with the abstractions provided by qualitative, symbolic models and their associated high-level control strategies. This will allow for effective management of the combinatorics due to the integration of a large number of ALS subsystems. By focusing control actions at different levels of detail and reactivity we can use faster: simpler responses at the lowest level and predictive but complex responses at the higher levels of abstraction. In particular, methods from model-based planning and scheduling can provide effective resource management over long time periods. We describe reference implementation of an advanced control system using the IDEA control architecture developed at NASA Ames Research Center. IDEA uses planning/scheduling as the sole reasoning method for predictive and reactive closed loop control. We describe preliminary experiments in planner-based control of ALS carried out on an integrated ALS simulation developed at NASA Johnson Space Center.

Muscettola, Nicola↗

NASA NTRS2004

A Software Architecture for Semiautonomous Robot Control

A software architecture has been developed to increase the safety and effectiveness with which tasks are performed by robots that are capable of functioning autonomously but sometimes are operated under control by humans. The control system of such a robot designed according to a prior software architecture has no way of taking account of how the environment has changed or what parts of a task were performed during an interval of control by a human, so that errors can occur (and, hence, safety and effectiveness jeopardized) when the human relinquishes control. The present architecture incorporates the control, task-planning, and sensor-based-monitoring features of typical prior autonomous-robot software architectures, plus features for updating information on the environment and planning of tasks during control by a human operator in order to enable the robot to track the actions taken by the operator and to be ready to resume autonomous operation with minimal error. The present architecture also provides a user interface that presents, to the operator, a variety of information on the internal state of the robot and the status of the task.

Kortenkamp, David↗

NASA NTRS2003

Working and Learning with Knowledge in the Lobes of a Humanoid's Mind

Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).

Ambrose, Robert↗

NASA NTRS2003

Experiments with an EVA Assistant Robot

Human missions to the Moon or Mars will likely be accompanied by many useful robots that will assist in all aspects of the mission, from construction to maintenance to surface exploration. Such robots might scout terrain, carry tools, take pictures, curate samples, or provide status information during a traverse. At NASA/JSC, the EVA Robotic Assistant (ERA) project has developed a robot testbed for exploring the issues of astronaut-robot interaction. Together with JSC's Advanced Spacesuit Lab, the ERA team has been developing robot capabilities and testing them with space-suited test subjects at planetary surface analog sites. In this paper, we describe the current state of the ERA testbed and two weeks of remote field tests in Arizona in September 2002. A number of teams with a broad range of interests participated in these experiments to explore different aspects of what must be done to develop a program for robotic assistance to surface EVA. Technologies explored in the field experiments included a fuel cell, new mobility platform and manipulator, novel software and communications infrastructure for multi-agent modeling and planning, a mobile science lab, an "InfoPak" for monitoring the spacesuit, and delayed satellite communication to a remote operations team. In this paper, we will describe this latest round of field tests in detail.

Burridge, Robert R.↗

NASA NTRS1994

Perception for mobile robot navigation: A survey of the state of the art

In order for mobile robots to navigate safely in unmapped and dynamic environments they must perceive their environment and decide on actions based on those perceptions. There are many different sensing modalities that can be used for mobile robot perception; the two most popular are ultrasonic sonar sensors and vision sensors. This paper examines the state-of-the-art in sensory-based mobile robot navigation. The first issue in mobile robot navigation is safety. This paper summarizes several competing sonar-based obstacle avoidance techniques and compares them. Another issue in mobile robot navigation is determining the robot's position and orientation (sometimes called the robot's pose) in the environment. This paper examines several different classes of vision-based approaches to pose determination. One class of approaches uses detailed, a prior models of the robot's environment. Another class of approaches triangulates using fixed, artificial landmarks. A third class of approaches builds maps using natural landmarks. Example implementations from each of these three classes are described and compared. Finally, the paper presents a completely implemented mobile robot system that integrates sonar-based obstacle avoidance with vision-based pose determination to perform a simple task.

Kortenkamp, David↗

NASA NTRS1994

Mobile robot exploration and navigation of indoor spaces using sonar and vision

Integration of skills into an autonomous robot that performs a complex task is described. Time constraints prevented complete integration of all the described skills. The biggest problem was tuning the sensor-based region-finding algorithm to the environment involved. Since localization depended on matching regions found with the a priori map, the robot became lost very quickly. If the low level sensing of the world is not working, then high level reasoning or map making will be unsuccessful.

Kortenkamp, David↗