Randy Sargent

Mission planning and target tracking for autonomous instrument placement

Future planetary rover missions, such as the upcoming Mars Science Laboratory, will require rovers to autonomously navigate to science targets specified from up to 10 meters away, and to place instruments against these targets with up to 1 centimeter precision. The current state of the art, demonstrated by the Mars Exploration Rover (MER) mission, typically requires three sols (Martian days) for approach and placement, with several communication cycles between the rovers and ground operations. The capability for goal level commanding of a rover to visit multiple science targets in a single sol represents a tenfold increase in productivity, and decreases daily operations costs. Such a capability requires a high degree of robotic autonomy: visual target tracking and navigation for the rover to approach the targets, mission planning for determining the most beneficial course of action given a large set of desired goals in the face of uncertainty, and robust execution for coping with variations in time and power consumption, as well as the possibility of failures in tracking or navigation due to occlusion or unexpected obstacles. We have developed a system that provides these features. The system uses a vision-based target tracker that recovers the 6-DOF transformations between the rover and the tracked targets as the rover moves, and an off-board planner that creates plans that are carried out on an on-board robust executive. The tracker comprises a feature based approach that tracks a set of interest points in 3D using stereo, with a shape based approach that registers dense 3D meshes. The off-board planner, in addition to generating a primary activity sequence, creates a large set of contingent, or alternate plans to deal with anticipated failures in tracking and the uncertainty in resource consumption. This paper describes our tracking and planning systems, including the results of experiments carried out using the K9 rover. These systems are part of a larger effort, which includes tools for target specification in 3D, ground-based simulation and plan verification, round-trip data tracking, rover software and hardware, and scientific visualization. The complete system has been shown to provide the capability of multiple instrument placements on rocks within a 10 meter radius, all within a single command cycle.

The XBC: a modern low-cost mobile robot controller

Much robotics research is carried out using either PICs and processors that are a decade or more out of date The alternative is custom built electronics that is expensive and/or must be reinvented every time a new project is begun. The XBC is a new design for a robot controller merging a modern ARM processor with an FPGA that allows high performance - especially in vision processing and motor control - for a cost similar to controllers with a fraction of its capabilities. Additionally, the XBC uses a new, and still free, software development system, already in wide use. The XBC is being mass produced (at least in research hardware terms) so it is readily available and does not require computer hardware or electronics skills in order to be obtained. This paper describes the system, its capabilities and some potential applications.

Terrain model registration for single cycle instrument placement

This paper presents an efficient and robust method for registration of terrain models created using stereovision on a planetary rover. Our approach projects two surface models into a virtual depth map, rendering the models, as they would be seen from a single range sensor. Correspondence is established based on which points project to the same location in the virtual range sensor. A robust norm of the deviations in observed depth is used as the objective function, and the algorithm searches for the rigid transformation, which minimizes the norm. An initial coarse search is done using rover pose information from odometry and orientation sensing. A fine search is done using Levenberg-Marquardt. Our method enables a planetary rover to keep track of designated science targets as it moves, and to hand off targets from one set of stereo cameras to another. These capabilities are essential for the rover to autonomously approach a science target and place an instrument in contact in a single command cycle.

Combined feature based and shape based visual tracker for robot navigation

We have developed a combined feature based and shape based visual tracking system designed to enable a planetary rover to visually track and servo to specific points chosen by a user with centimeter precision. The feature based tracker uses invariant feature detection and matching across a stereo pair, as well as matching pairs before and after robot movement in order to compute an incremental 6-DOF motion at each tracker update. This tracking method is subject to drift over time, which can be compensated by the shape based method. The shape based tracking method consists of 3D model registration, which recovers 6-DOF motion given sufficient shape and proper initialization. By integrating complementary algorithms, the combined tracker leverages the efficiency and robustness of feature based methods with the precision and accuracy of model registration. In this paper, we present the algorithms and their integration into a combined visual tracking system.

Instrument deployment for Mars Rovers

Future Mars rovers, such as the planned 2009 MSL rover, require sufficient autonomy to robustly approach rock targets and place an instrument in contact with them. It took the 1997 Sojourner Mars rover between 3 and 5 communications cycles to accomplish this. This paper describes the NASA Ames approach to robustly accomplishing single cycle instrument deployment, using the K9 prototype Mars rover. An off-board 3D site model is used to select science targets for the rover. K9 navigates to targets using deduced reckoning, and autonomously assesses the target area to determine where to place an arm mounted microscopic camera. Onboard K9 is a resource cognizant conditional executive, which extends the complexity and duration of operations that a can be accomplished without intervention from mission control.

The importance of fast vision in winning the First Micro-Robot World Cup Soccer Tournament

Abstract This paper describes the Newton Labs entry in the 1996 MIROSOT Micro-Robot World Cup Soccer Tournament (http://www.mirosot.org), which won first place. Control of the three robot players is centralized; this requires relatively high bandwidth connections to the robots, as well as fast spatial information at the central controller. Spatial sensing is accomplished by use of the Cognachrome Vision Tracking System, which is capable of tracking the positions and orientations of several objects at the full NTSC frame rate of 60 Hz.

Respawn: A Distributed Multi-resolution Time-Series Datastore

As sensor networks gain traction and begin to scale, we will be increasingly faced with challenges associated with managing large-scale time-series data. In this paper, we present a cloud-to-edge partitioned architecture called Respawn that is capable of serving large amounts of time-series data from a continuously updating datastore with access latencies low enough to support interactive real-time visualization. Respawn targets sensing systems where resource-constrained edge node devices may only have limited or intermittent network connections linking them to a cloud-backend. The cloud-backend provides aggregate storage and transparent dispatching of data queries to edge node devices. Data is downsampled as it enters the system creating a multi-resolution representation capable of lowlatency range-base queries. Lower-resolution aggregate data is automatically migrated from edge nodes to the cloud-backend both for improved consistency and caching. In order to further mask latency from users, edge nodes automatically identify and migrate blocks of data that contain statistically interesting features. We show through simulation and micro-benchmarking that Respawn is able to run on ARM-based edge node devices connected to a cloud-backend with the ability to serve thousands of clients and terabytes of data with sub-second latencies.

Terapixel Imaging of Cosmological Simulations

The increasing size of cosmological simulations has led to the need for new visualization techniques. We focus on smoothed particle hydrodynamic (SPH) simulations run with the GADGET code and describe methods for visually accessing the entire simulation at full resolution. The simulation snapshots are rastered and processed on supercomputers into images that are ready to be accessed through a Web interface (GigaPan). This allows any scientist with a Web browser to interactively explore simulation data sets in both spatial and temporal dimensions and data sets which in their native format can be hundreds of terabytes in size or more. We present two examples, the first a static terapixel image of the MassiveBlack simulation, a P-GADGET SPH simulation with 65 billion particles, and the second an interactively zoomable animation of a different simulation with more than 1000 frames, each a gigapixel in size. Both are available for public access through the GigaPan Web interface. We also make our imaging software publicly available.

The Spirit of Bolivia: Complex Behavior Through Minimal Control

The “Spirit of Bolivia” is a robotic soccer team which demonstrates minimally comprehensive team behavior. By this we mean that each member of the team makes progress towards team goals, and obstructs progress of the opponent, by interacting constructively with team-mates and in a sportsmanlike manner with opposing players. This complex behavior is achieved with simple on-board processors running very small behavior-based control programs; team behaviors are achieved without explicit communication. Externalization — the use of the environment as its own best model — and tolerance — a bias towards reducing the need for accurate information rather than attempting to recognize or correct noisy information — are the keys to robustness and sophistication of team behavior.

Community-Empowered Air Quality Monitoring System

Developing information technology to democratize scientific knowledge and support citizen empowerment is a challenging task. In our case, a local community suffered from air pollution caused by industrial activity. The residents lacked the technological fluency to gather and curate diverse scientific data to advocate for regulatory change. We collaborated with the community in developing an air quality monitoring system which integrated heterogeneous data over a large spatial and temporal scale. The system afforded strong scientific evidence by using animated smoke images, air quality data, crowdsourced smell reports, and wind data. In our evaluation, we report patterns of sharing smoke images among stakeholders. Our survey study shows that the scientific knowledge provided by the system encourages agonistic discussions with regulators, empowers the community to support policy making, and rebalances the power relationship between stakeholders.