Adaptive Sensing of Time Series with Application to Remote Exploration
No abstract available
autonomous exploration↗
Engineering topics
Wettergreen, David
Publications and source records attributed to Wettergreen, David.
Adaptive Sensing of Time Series with Application to Remote Exploration
We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.
artificial intelligence↗
Initial Results from Vision-based Control of the Marsokhod Rover
A geologist characterizing a field site typically wanders from one interesting geologic feature to another. Performing geology remotely with a mobile robot, we have observed the same behavior: geologists see a visually-interesting feature and wish to approach it for closer inspection. To date, navigating a mobile robot to a visually-interesting feature has been accomplished by driving to a location close to the feature. This introduces two problems: assigning a location to the feature and navigating the rover to that location. In practice, solutions to both of these problems are susceptable to positional error. Fundamentally, we can see where we want the robot to go, but it is difficult to precisely quantify where either the target or the robot are located. The development of vision-based control of robot manipulators suggests an alternative approach for mobile robot explorers. We have developed a vision-based control system that enables the Marsokhod rover to drive to within sampling distance of visually-designated rock or natural feature. We will describe this system and our initial results using it during a field experiment in the Painted Desert of Arizona.
Wettergreen, David↗
Planning strategies for the Ambler walking robot
A hierarchy of planning strategies is proposed and explained for a walking robot called the Ambler. The hierarchy decomposes planning into levels of trajectory, gait, and footfall. An abstraction of feasible traversability allows the Ambler's trajectory planner to identify acceptable trajectories by finding paths that guarantee footfalls without specifying exactly which footfalls. Leg and body moves that achieve this trajectory can be generated by the Ambler's gait planner, which incorporates pattern constraints and measures of utility to search for the best next move. By combining constraints from the quality and details of the terrain, the Ambler's footfall planner can select footfalls that insure stability and remain within the tolerances of the gait.
Wettergreen, David↗