Joseph Carsten

Global Path Planning on Board the Mars Exploration Rovers

In January 2004, NASAs twin Mars exploration rovers (MERs), spirit and opportunity, began searching the surface of Mars for evidence of past water activity. In order to localize and approach scientifically interesting targets, the rovers employ an on-board navigation system. Given the latency in sending commands from Earth to the Martian rovers (and in receiving return data), a high level of navigational autonomy is desirable. Autonomous navigation with hazard avoidance (AutoNav) is currently performed using a local path planner called GESTALT (grid-based estimation of surface traversability applied to local terrain). GESTALT uses stereo cameras to evaluate terrain safety and avoid obstacles. GESTALT works well to guide the rovers around narrow and isolated hazards, however, it is susceptible to failure when clusters of closely spaced, non-traversable rocks form extended obstacles. In May 2005, a new technology task was initiated at the Jet Propulsion Laboratory to address this limitation. A version of the Carnegie Mellon University Field D* global path planner has been integrated into MER flight software, enabling simultaneous local and global planning during AutoNav. A revised version of AutoNav was uploaded to the rovers during the summer of 2006. This paper describes how global planning was integrated into the MER flight software, and presents results of testing the improved AutoNav system using the MER Surface System TestBed rover.

3D Field D: Improved Path Planning and Replanning in Three Dimensions

We present an interpolation-based planning and replanning algorithm that is able to produce direct, low-cost paths through three-dimensional environments. Our algorithm builds upon recent advances in 2D grid-based path planning and extends these techniques to 3D grids. It is often the case for robots navigating in full three-dimensional environments that moving in some directions is significantly more difficult than others (e.g. moving upwards is more expensive for most aerial vehicles). Thus, we also provide a facility to incorporate such characteristics into the planning process. Along with the derivation of the 3D interpolation function used by our planner, we present a number of results demonstrating its advantages and real-time capabilities

Mars Science Laboratory Algorithms and Flight Software for Autonomously Drilling Rocks

One of the goals of the Mars Science Laboratory (MSL) mission is to collect powderized samples from the interior of rocks in order to deliver these samples to onboard science instruments. This paper describes the algorithms and software used to control the drill, which is the component of the sample collection and delivery system that directly interacts with rocks to create and acquire powderized samples from their interior. This is the first time that autonomous drilling of rocks has ever been performed on another planet. One of the most important components of the algorithm used for drilling is a force feedback control system used to regulate the force applied to the rock during drilling. This algorithm and all of the other algorithms and software used to enable the process of robustly, efficiently, and autonomously drilling into rocks with a priori unknown and widely varying properties are described in detail in this paper. Results are shown from drilling rocks using the drill software on testbed hardware on Earth as part of the software development process. Results are also shown from the first holes drilled with the flight vehicle on Mars, thus successfully demonstrating the first extraterrestrial autonomous drilling of a rock.

The Phoenix Mars Lander Robotic Arm

The Phoenix Mars Lander Robotic Arm (RA) has operated for 149 sols since the Lander touched down on the north polar region of Mars on May 25, 2008. During its mission it has dug numerous trenches in the Martian regolith, acquired samples of Martian dry and icy soil, and delivered them to the Thermal Evolved Gas Analyzer (TEGA) and the Microscopy, Electrochemistry, and Conductivity Analyzer (MECA). The RA inserted the Thermal and Electrical Conductivity Probe (TECP) into the Martian regolith and positioned it at various heights above the surface for relative humidity measurements. The RA was used to point the Robotic Arm Camera to take images of the surface, trenches, samples within the scoop, and other objects of scientific interest within its workspace. Data from the RA sensors during trenching, scraping, and trench cave-in experiments have been used to infer mechanical properties of the Martian soil. This paper describes the design and operations of the RA as a critical component of the Phoenix Mars Lander necessary to achieve the scientific goals of the mission.

Test and validation of the Mars Science Laboratory Robotic Arm

The Mars Science Laboratory Robotic Arm (RA) is a key component for achieving the primary scientific goals of the mission. The RA supports sample acquisition by precisely positioning a scoop above loose regolith or accurately preloading a percussive drill on Martian rocks or rover-mounted organic check materials. It assists sample processing by orienting a sample processing unit called CHIMRA through a series of gravity-relative orientations and sample delivery by positioning the sample portion door above an instrument inlet or the observation tray. In addition the RA facilitates contact science by accurately positioning the dust removal tool, Alpha Particle X-Ray Spectrometer (APXS) and the Mars Hand Lens Imager (MAHLI) relative to surface targets. In order to fulfill these seemingly disparate science objectives the RA must satisfy a variety of accuracy and performance requirements. This paper describes the necessary arm requirement specification and the test campaign to demonstrate these requirements were satisfied.

In-situ operations and planning for the Mars Science Laboratory Robotic Arm: The first 200 sols

The Robotic Arm (RA) has operated for more than 200 Martian solar days (or sols) since the Mars Science Laboratory rover touched down in Gale Crater on August 5, 2012. During the first seven months on Mars the robotic arm has performed multiple contact science sols including the positioning of the Alpha Particle X-Ray Spectrometer (APXS) and/or Mars Hand Lens Imager (MAHLI) with respect to rocks or loose regolith targets. The RA has supported sample acquisition using both the scoop and drill, sample processing with CHIMRA (Collection and Handling for In- Situ Martian Rock Analysis), and delivery of sample portions to the observation tray, and the SAM (Sample Analysis at Mars) and CHEMIN (Chemistry and Mineralogy) science instruments. This paper describes the planning and execution of robotic arm activities during surface operations, and reviews robotic arm performance results from Mars to date.

In situ robotic arm operations

This article compares and contrasts the operations of the robotic manipulators on the Mars Phoenix Lander and Mars Exploration Rovers (MERs), Spirit and Opportunity. Unlike the MERs, the Phoenix Mars Lander stays in one spot at a particular geographic location on the Martian surface with exploration emphasis on vertical mobility sampling. In this article the operations of Phoenix robotic arm (RA) were described during the prime mission and compare and contrast it with MER instrument deployment device (IDD) operations. In addition, the technology gaps were identified in operations and deployment of in situ manipulators in planetary exploration.

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.

Topological Global Localization for Subterranean Voids

The need for reliable maps of subterranean spaces too hazardous for humans to occupy has motivated the development of robotic mapping tools. For such systems to be fully autonomous, they must be able to deal with all varieties of subterranean environments, including those containing loops. This paper presents an approach for an autonomous mobile robot to determine if the area currently being explored has been previously visited. Combined with other techniques in topological mapping, this approach will allow for the fully autonomous general exploration of subterranean spaces. Data collected from a research coal mine is used to experimentally verify our approach.

Onboard centralized frame tree database for intelligent space operations of the Mars Science Laboratory Rover.

Planetary surface science operations performed by robotic space systems frequently require pointing cameras at various objects and moving a robotic arm end effector tool toward specific targets. Earlier NASA Mars Exploration Rovers did not have the ability to compute actual coordinates for given object coordinate frame names and had to be provided with explicit coordinates. Since it sometimes takes hours to more than a day to get final approval of certain calculated coordinates for command uplink via the Earth-based mission operations procedures, a highly desired enhancement for future rovers was to have the onboard automated capability to compute the coordinates for a given frame name. The Mars Science Laboratory (MSL) rover mission is the first to have a centralized coordinate transform database to maintain the knowledge of spatial relations. This onboard intelligence significantly simplifies communication and control between Earth-based human mission operators and the robotic rover on Mars by supporting higher level abstraction of commands using object and target names instead of coordinates. More specifically, the spatial relations of many object frames are represented hierarchically in a tree data structure, called the frame tree. Individual frame transforms are populated by their respective modules that have specific knowledge of the frames. Through this onboard centralized frame tree database, client modules can query transforms between any two frames and support spacecraft commands that use any frames maintained in the frame tree. Various operational examples in the MSL mission that have greatly benefitted from this onboard centralized frame tree database are presented.