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This paper describes recent work undertaken at the Jet Propulsion Laboratory in Pasadena, CA in the area of increased rover autonomy for planetary surface operations.
Autonomy technology for high-level, closed-loop control of spacecraft offers considerable benefits to space-flight projects. Those benefits can enable whole new classes of missions; however, they are not without cost.
This paper describes experiments that quantify the improvement that autonomous behaviors enable in the amount of user interaction required to navigate a robot in urban environments. Many papers have discussed various ways to measure the absolute level of autonomy of a system; we measured the relative improvement of autonomous behaviors over teleoperation across multiple traverses of the same course. We performed four runs each on an 'easy' course and a 'hard' course, where half the runs were teleoperated and half used more autonomous behaviors. Statistics show 40-70% reductions in the amount of time the user interacts with the control station; however, with the behaviors tested, user attention remained on the control station even when he was not interacting. Reducing the need for attention will require better obstacle detection and avoidance and better absolute position estimation.
This viewgraph presentation covers the following topics: Coupled Layer Architecture for Robotic Autonomy CLARAty system at the functional layer and the decision layer; and CLEaR - AI Planning and Schedule - Task Based Control, A demonstration is of the operation of the system is given, with viewgraphs of the rover movement control.
Space mission operations are extremely labor and knowledge-intensive and are driven by the ground and flight systems. Inclusion of an autonomy capability can have dramatic effects on mission operations. We describe the prior, labor and knowledge intensive mission operations flow for the Earth Observing-1 (EO-1) spacecraft as well as the new autonomous operations as part of the Autonomous Sciencecraft Experiment.
Breakthrough autonomy technologies enable a new range of spire missions that acquire vast amounts of data and return only the most scientifically important data to Earth. These missions would monitor science phenomena in great detail (either with frequent observations or at extremely high spatial resolution) and onboard analyze the data to detect specific science events of interest. These missions would monitor volcanic eruptions, formation and movement of aeolian features. and atmospheric phenomena. The autonomous spacecraft would respond to science events by planning its future operations to revisit or perform complementary observations. In this paradigm, the spacecraft represents the scientists agent enabling optimization of the downlink data volume resource. This paper describes preliminary efforts to define and design such missions.
This paper presents an architecture and a set of technology for performing autonomous science and commanding for a planetary rover. The MER rovers have outperformed all expectations by lasting over 1100 sols (or Martian days), which is an order of magnitude longer than their original mission goal. The longevity of these vehicles will have significant effects on future mission goals, such as objectives for the Mars Science Laboratory rover mission (scheduled to fly in 2009) and the Astrobiology Field Lab rover mission (scheduled to potentially fly in 2016). Common objectives for future rover missions to Mars include the handling of opportunistic science, long-range or multi-sol driving, and onboard fault diagnosis and recovery. To handle these goals, a number of new technologies have been developed and integrated as part of the CLARAty architecture. CLARAty is a unified and reusable robotic architecture that was designed to simplify the integration, testing and maturation of robotic technologies for future missions. This paper focuses on technology comprising the CLARAty Decision Layer, which was designed to support and validate high-level autonomy technologies, such as automated planning and scheduling and onboard data analysis.
On-water demonstration of a wide range of mission-proven, advanced technologies at TRL 5+ that provide a total integrated, modular approach to effectively address the majority of the key needs for full mission-level autonomous, cross-platform control of USV s. Wide baseline stereo system mounted on the ONR USSV was shown to be an effective sensing modality for tracking of dynamic contacts as a first step to automated retrieval operations. CASPER onboard planner/replanner successfully demonstrated realtime, on-water resource-based analysis for mission-level goal achievement and on-the-fly opportunistic replanning. Full mixed mode autonomy was demonstrated on-water with a seamless transition between operator over-ride and return to current mission plan. Autonomous cooperative operations for fixed asset protection and High Value Unit escort using 2 USVs (AMN1 & 14m RHIB) were demonstrated during Trident Warrior 2010 in JUN 2010
Unmanned aerial systems, advanced cockpits, and air traffic management are all seeing dramatic increases in automation. However, while automation may take on some tasks previously performed by humans, humans will still be required to remain in the system for the foreseeable future. The collaboration between humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. This paper applies a methodology for identifying HAT patterns to an advanced cockpit project.
Unmanned aerial systems, robotics, advanced cockpits, and air traffic management are all examples of domains that are seeing dramatic increases in automation. While automation may take on some tasks previously performed by humans, humans will still be required, for the foreseeable future, to remain in the system. The collaboration with humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. This paper applies a methodology for identifying HAT patterns to an advanced cockpit project.
This is a powerpoint presentation that highlights autonomy across the 15 NASA technology roadmaps, including specific examples of projects (past and present) at NASA Ames Research Center. The NASA technology roadmaps are located here: http:www.nasa.govofficesocthomeroadmapsindex.html
As part of the Air Force - NASA Bi-Annual Research Council Meeting, slides will be presented on recent Reduced Crew Operations (RCO) work. Unmanned aerial systems, robotics, advanced cockpits, and air traffic management are all examples of domains that are seeing dramatic increases in automation. While automation may take on some tasks previously performed by humans, humans will still be required, for the foreseeable future, to remain in the system. The collaboration with humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. A methodology for identifying HAT patterns to an advanced cockpit project is discussed.
Known problems with automation include lack of mode awareness, automation brittleness, and risk of miscalibrated trust. Human-Autonomy Teaming (HAT) is essential for improving these problems. We have identified some critical components of HAT and ran a part-task study to introduce these components to a ground station that supports flight following of multiple aircraft. Our goal was to demonstrate, evaluate, and refine HAT principles. This presentation provides a brief summary of the study and initial findings.
Over the last three years, we have been investigating the operational concept of crew self-scheduling as a method of increasing crew autonomy for future exploration missions. Through Playbook, a planning and scheduling software tool, we have incrementally increased the ability for Earth analog mission crews to modify their schedules. Playbook allows the crew to add new activities from scratch, add new activities or groups of activities through a Task List, and reschedule or reassign flexible activities. The crew is also able to identify if plan modifications create violations, i.e., plan constraints not being met. This paper summarizes our observations with qualitative evidence from four NASA Extreme Environment Mission Operations (NEEMO) analog missions that supported self-scheduling as a feasible operational concept.
Automation has entered nearly every aspect of our lives, but it often remains hard to understand. Why is this? Automation is often brittle, requiring constant human oversight to assure it operates as intended. This oversight has become harder as automation has become more complicated. To resolve this problem, Human-Autonomy Teaming (HAT) has been proposed. HAT looks to make automation act as more of a teammate, by having it communicate with human operators in a more human, goal-directed, manner which provides transparency into the reasoning behind automated recommendations and actions. This, in turn, permits more trust in the automation when it is appropriate, and less when it is not, allowing a more targeted supervision of automated functions. This paper proposes a framework for HAT, incorporating two key tenets: bi-directional communication, and operator directed authority. We have successfully applied these tenets to integrating the autonomous constrained flight planner (an aide for planning diverts) into a dispatch station. We propose the development of general design patterns that may allow these results to be generalized to domains such as photography and automotive navigation. While these domains are very different, we find application of our HAT tenets provides a number of opportunities for improving interaction between human operators and automation.
Managing aircraft is becoming more complex with increasingly sophisticated automation responsible for more flight tasks. With this increased complexity, it is becoming more difficult for operators to understand what the automation is doing and why. Human involvement with increasingly autonomous systems must adjust to allow for a more dynamic relationship involving cooperation and teamwork. As part of an ongoing project to develop a framework for human-autonomy teaming (HAT) in aviation, a part-task study was conducted to demonstrate, evaluate and refine proposed critical aspects of HAT. These features were built into an automated recommender system on a ground station available from previous studies. Participants performed a flight-following task once with the original ground station (i.e., No HAT condition) and once with the HAT features enabled (i.e., HAT condition). Behavioral and subjective measures were collected; subjective measures are presented here. Overall, participants preferred the ground station with HAT features enabled compared to the station without the HAT features. Participants reported that the HAT displays and automation were preferred for keeping up with operationally important issues. Additionally, participants reported that the HAT displays and automation provided enough situation awareness to complete the task and reduced workload relative to the No HAT baseline.
Over the last three years, we have been investigating the operational concept of crew self-scheduling as a method of increasing crew autonomy for future exploration missions. Through Playbook, a planning and scheduling software tool, we have incrementally increased the ability for Earth analog mission crews to modify their schedules. Playbook allows the crew to add new activities from scratch, add new activities or groups of activities through a Task List, and reschedule or reassign flexible activities. The crew is also able to identify if plan modifications create violations, i.e., plan constraints not being met. This paper summarizes our observations with qualitative evidence from four NASA Extreme Environment Mission Operations (NEEMO) analog missions that supported self-scheduling as a feasible operational concept.
This presentation is given at a NASA DLR (German Aerospace Center) meeting at NASA ARC on March 14, 2017. The presentation provides an overview of the Advanced Control and Evolvable Systems (ACES) group at NASA ARC and the research areas in UAS autonomy, stall recovery guidance, and flexible aircraft flight control.