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Helmick, Daniel

Publications and source records attributed to Helmick, Daniel.

9 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Software System for the Mars 2020 Mission Sampling and Caching Testbeds

The development of the Sampling and Caching Subsystem (SCS) of the Mars 2020 Rover Mission is highly dependent on testing of prototype hardware and software operating in explicit conditions as part of integrated testbeds. To achieve relevant integration of hardware and software while maintaining rapid algorithm development capabilities and high testing throughput, the Controls and Autonomy for Sample Acquisition and Handling (CASAH) software system was developed. CASAH is an implementation of the Intelligent Robotics System Architecture (IRSA),which mimics JPL Flight Software (FSW) in that it is divided into hierarchical modules that run separate processes that communicate via message passing, each module is assigned an owner that is a single developer, and the operator initiates requests via a text-based interface that interprets sequences of commands.IRSA enables a modular breakdown of CASAH that follows that of 2020 Flight Software,so developers can take an algorithm from a module in CASAH and re-code it into the same module in FSW. As deployment of CASAH has grown to ten testbeds - each with different hardware and objectives - bottom-up design decisions have been intentionally made to keep the system lightweight and maintainable by a very small team. To date, CASAH has been used to run 1393 different tests. This work describes CASAH, the testbeds and functionality it supports, the tools used to manage the development and sharing of code, and the features of the software. Lessons learned over the past three years of development and deployment are provided.

Vieira, Peter↗
NASA NTRS2013

Mars Science Laboratory CHIMRA/IC/DRT Flight Software for Sample Acquisition and Processing

The design methodologies of using sequence diagrams, multi-process functional flow diagrams, and hierarchical state machines were successfully applied in designing three MSL (Mars Science Laboratory) flight software modules responsible for handling actuator motions of the CHIMRA (Collection and Handling for In Situ Martian Rock Analysis), IC (Inlet Covers), and DRT (Dust Removal Tool) mechanisms. The methodologies were essential to specify complex interactions with other modules, support concurrent foreground and background motions, and handle various fault protections. Studying task scenarios with multi-process functional flow diagrams yielded great insight to overall design perspectives. Since the three modules require three different levels of background motion support, the methodologies presented in this paper provide an excellent comparison. All three modules are fully operational in flight.

sample processing↗
NASA NTRS2009

More About Reconfigurable Exploratory Robotic Vehicles

Modular exploratory robotic vehicles that will be able to reconfigure themselves in the field are undergoing development. Proposed for use in exploration of the surfaces of Mars and other remote planets, these vehicles and others of similar design could also be useful for exploring hostile terrain on Earth.

Howard, Ayanna↗
NASA NTRS2008

Visual Feedback for Rover-based Coring

Technology for coring from a low-mass rover has been developed to enable core sample acquisition where a planetary rover experiences moderate slip during the coring operation. A new stereo vision technique, Absolute Motion Visual Odometry, is used to measure rover slip during coring and the slip is accommodated through corresponding arm pose updating. Coring rate is controlled by feedback of themeasured force of the coring tool against the environment. Test results in the JPL Marsyard show for the first time that coring from a low-mass rover with slip is feasible.

sampling↗
NASA NTRS2007

Learning and Prediction of Slip from Visual Information

This paper presents an approach for slip prediction from a distance for wheeled ground robots using visual information as input. Large amounts of slippage which can occur on certain surfaces, such as sandy slopes, will negatively affect rover mobility. Therefore, obtaining information about slip before entering such terrain can be very useful for better planning and avoiding these areas. To address this problem, terrain appearance and geometry information about map cells are correlated to the slip measured by the rover while traversing each cell. This relationship is learned from previous experience, so slip can be predicted remotely from visual information only. The proposed method consists of terrain type recognition and nonlinear regression modeling. The method has been implemented and tested offline on several off-road terrains including: soil, sand, gravel, and woodchips. The final slip prediction error is about 20%. The system is intended for improved navigation on steep slopes and rough terrain for Mars rovers.

rover↗
NASA NTRS2006

A comparison of force sensing techniques for planetary manipulation

Five techniques for sensing forces with a manipulator are compared analytically and experimentally. The techniques compared are: a six-axis wrist force/torque sensor, joint torque sensors, link strain gauges, motor current sensors, and flexibility modeling. The accuracy and repeatability fo each technique is quantified and compared.

force sensing↗
NASA NTRS2006

Learning to predict slip for ground robots

In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do that, the information of terrain appearance and geometry regarding some location is correlated to the slip measured by the rover while this location is being traversed. This relationship is learned from previous experience, so slip can be predicted later at a distance from visual information only.

robots↗
NASA NTRS2005

Path Following with Slip Compensation for a Mars Rover

A software system for autonomous operation of a Mars rover is composed of several key algorithms that enable the rover to accurately follow a designated path, compensate for slippage of its wheels on terrain, and reach intended goals. The techniques implemented by the algorithms are visual odometry, full vehicle kinematics, a Kalman filter, and path following with slip compensation. The visual-odometry algorithm tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs, by use of a maximum-likelihood motion-estimation algorithm. The full-vehicle kinematics algorithm estimates motion, with a no-slip assumption, from measured wheel rates, steering angles, and angles of rockers and bogies in the rover suspension system. The Kalman filter merges data from an inertial measurement unit (IMU) and the visual-odometry algorithm. The merged estimate is then compared to the kinematic estimate to determine whether and how much slippage has occurred. The kinematic estimate is used to complement the Kalman-filter estimate if no statistically significant slippage has occurred. If slippage has occurred, then a slip vector is calculated by subtracting the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the wheel velocities and steering angles needed to compensate for slip and follow the desired path.

Helmick, Daniel↗