7,148 research outputs found
Pilot interaction with automated airborne decision making systems
The use of advanced software engineering methods (e.g., from artificial intelligence) to aid aircraft crews in procedure selection and execution is investigated. Human problem solving in dynamic environments as effected by the human's level of knowledge of system operations is examined. Progress on the development of full scale simulation facilities is also discussed
Overcoming barriers and increasing independence: service robots for elderly and disabled people
This paper discusses the potential for service robots to overcome barriers and increase independence of
elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly
people and advances in technology which will make new uses possible and provides suggestions for some of these new
applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses
the complementarity of assistive service robots and personal assistance and considers the types of applications and
users for which service robots are and are not suitable
A heuristic distributed task allocation method for multivehicle multitask problems and its application to search and rescue scenario
Using distributed task allocation methods for cooperating
multivehicle systems is becoming increasingly attractive.
However, most effort is placed on various specific experimental
work and little has been done to systematically analyze the
problem of interest and the existing methods. In this paper, a
general scenario description and a system configuration are first
presented according to search and rescue scenario. The objective
of the problem is then analyzed together with its mathematical
formulation extracted from the scenario. Considering the requirement
of distributed computing, this paper then proposes a novel
heuristic distributed task allocation method for multivehicle multitask
assignment problems. The proposed method is simple and
effective. It directly aims at optimizing the mathematical objective
defined for the problem. A new concept of significance is
defined for every task and is measured by the contribution to
the local cost generated by a vehicle, which underlies the key
idea of the algorithm. The whole algorithm iterates between a
task inclusion phase, and a consensus and task removal phase,
running concurrently on all the vehicles where local communication
exists between them. The former phase is used to include
tasks into a vehicle’s task list for optimizing the overall objective,
while the latter is to reach consensus on the significance value of tasks for each vehicle and to remove the tasks that have
been assigned to other vehicles. Numerical simulations demonstrate
that the proposed method is able to provide a conflict-free
solution and can achieve outstanding performance in comparison
with the consensus-based bundle algorithm
An Integrated Traverse Planner and Analysis Tool for Planetary Exploration
Future planetary explorations will require surface traverses of unprecedented frequency, length, and duration. As a result, there is need for exploration support tools to maximize productivity, scientific return, and safety. The Massachusetts Institute of Technology is currently developing such a system, called the Surface Exploration Traverse Analysis and Navigation Tool (SEXTANT). The goal of this system is twofold: to allow for realistic simulations of traverses in order to assist with hardware design, and to give astronauts an aid that will allow for more autonomy in traverse planning and re-planning. SEXTANT is a MATLAB-based tool that incorporates a lunar elevation model created from data from the Lunar Orbiter Laser Altimeter instrument aboard the Lunar Reconnaissance Orbiter spacecraft. To assist in traverse planning, SEXTANT determines the most efficient path across a planetary surface for astronauts or transportation rovers between user-specified Activity Points. The path efficiency is derived from any number of metrics: the traverse distance, traverse time, or the explorer’s energy consumption. The generated path, display of traverse obstacles, and selection of Activity Points are visualized in a 3D mapping
interface. After a traverse has been planned, SEXTANT is capable of computing the most efficient path back home, or “walkback”, from any point along the traverse – an important capability for emergency operations. SEXTANT also has the ability to determine shadowed and sunlit areas along a lunar traverse. This data is used to compute the thermal load on suited astronauts and the solar power generation capacity of rovers over the entire traverse. These both relate directly to the explorer’s consumables, which place strict constraints on the traverse. This paper concludes by presenting three example traverses, detailing how SEXTANT can be used to plan and modify paths for both explorer types.Massachusetts Institute of Technology (Donald W. Douglas Fellowship)National Space Biomedical Research Institute (Grant HFP00003
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