Rendezvous Lidar Sensor System for Terminal ...

Rendezvous Lidar Sensor System for Terminal Rendezvous, Capture, and Berthing to the International Space Station Andrew C. M. Allen*a, Christopher Langleya, Raja Mukherjia, Allen B. Taylora, Manickam Umasuthana, Timothy D. Barfootb a MDA Space Missions, 9445 Airport Rd., Brampton, Ont., Canada L6S 4J3; bUniversity of Toronto Institute for Aerospace Studies, 4925 Dufferin Street, Toronto, Ontario, Canada M3H 5T6 ABSTRACT The Rendezvous Lidar System (RLS), a high-performance scanning time-of-flight lidar jointly developed by MDA and Optech, was employed successfully during the XSS-11 spacecraft’s 23-month mission. Ongoing development of the RLS mission software has resulted in an integrated pose functionality suited to safety-critical applications, specifically the terminal rendezvous of a visiting vehicle with the International Space Station (ISS). This integrated pose capability extends the contribution of the lidar from long-range acquisition and tracking for terminal rendezvous through to final alignment for docking or berthing. Innovative aspects of the technology that were developed include: 1) efficacious algorithms to detect, recognize, and compute the pose of a client spacecraft from a single scan using an intelligent search of candidate solutions, 2) automatic scene evaluation and feature selection algorithms and software that assist mission planners in specifying accurate and robust scan scheduling, and 3) optimal pose tracking functionality using knowledge of the relative spacecraft states. The development process incorporated the concept of sensor system bandwidth to address the sometimes unclear or misleading specifications of update rate and measurement delay often cited for rendezvous sensors. Because relative navigation sensors provide the measured feedback to the spacecraft GN&C, we propose a new method of specifying the performance of these sensors to better enable a full assessment of a given sensor in the closed-loop control for any given vehicle. This approach, and the tools and methods enabling it, permitted a rapid and rigorous development and verification of the pose tracking functionality. The complete system was then integrated and demonstrated in the MDA space vision facility using the flight-representative engineering model RLS lidar sensor. Keywords: rendezvous, proximity operations, lidar, ladar, sensor, berthing, capture, docking, navigation, GNC

1. INTRODUCTION In previous articles, upgrades to the Rendezvous Lidar System (RLS) have been discussed regarding improvements to the performance and extended functionality [1][2]. Indeed, recent work has demonstrated the feasibility of reducing the sensor’s minimum range to 0.5 meters while improving response while operating facing the solar disk. The RLS, originally designed for rendezvous and proximity operations between a maneuvering spacecraft and an unprepared passive spacecraft, has been further developed to extend its capabilities to include full relative stationkeeping of two spacecraft which permits capture and berthing. This capability does not rely on the presence of any visual targets on the passive spacecraft. Rather, the geometry of the vehicle is matched against the measured range images and the resulting match permits the determination of the relative pose (position and orientation) of the two vehicles. This permits the system to be used whether or not the passive spacecraft has visual targets or whether any existing visual targets are in the lidar field of view. Specific examples of operations needing this capability include on-orbit servicing of satellites and capture and berthing of cargo vehicles via the Space Station Remote Manipulator System (SSRMS). In this paper, we will focus on the latter case: an approaching or departing autonomous cargo vehicle positioning itself inside the capture envelope of the SSRMS with sufficiently high accuracy and sufficiently low residual drift to permit safe capture and rigidization within a specified operational window. In addition to the relative positioning required at terminal approach, the pose measurements confer the additional benefit of providing range and bearing to a specific frame of reference on the passive spacecraft during the proximity operations without requiring any visual target infrastructure. That is, pose *

[email protected]; phone 1-905-790-2800 ext. 4780; fax 1-905-790-4400; http://sm.mdacorporation.com/ Sensors and Systems for Space Applications II, edited by Richard T. Howard, Pejmun Motaghedi, Proc. of SPIE Vol. 6958, 69580S, (2008) · 0277-786X/08/$18 · doi: 10.1117/12.777208

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measurements permit the approaching spacecraft to save time and propellant by planning burns relative to, for example, a berthing or docking interface on a space station or to the center of mass of a disabled satellite. This capability is a benefit when compared to a skin-tracking radar system or a lidar that provides only range and bearing to the centroid of the target. A similar, but simpler, technique has been used earlier to demonstrate the capture of a sample canister in Mars orbit using only a lidar [3]. The addition of pose measurement capability to the lidar extends the usefulness of a medium range rendezvous and proximity operations sensor into the near range. For some scenarios this means that one sensor can be used as the primary relative navigation sensor throughout the operation thereby saving mass, power, and the operational complexity of handing off from one sensor to another as range-to-target decreases. Even in scenarios requiring switching between multiple sensors, extending the functional range of a sensor increases operational robustness by increasing the hand-off overlap range between sensors. Larger overlap allows greater consistency checking and more confidence that the integrated system is functioning nominally.

2. RENDEZVOUS LIDAR SYSTEM XSS-11 (eXperimental Satellite System 11) was an Air Force Research Laboratory (AFRL) microsatellite built by Lockheed Martin Astronautics in Denver. The 138-kilogram spacecraft was inserted into orbit with an initial orbital period of 102 minutes, an apogee of 875 kilometers, a perigee of 839 kilometers, and an inclination of 98.8°. The launch vehicle was an Orbital Sciences Minotaur rocket, a modified Minuteman 2 ICBM, from Vandenberg AFB in early April 2005. The mission duration exceeded the design mission life of 12-18 months.

Figure 1: XSS-11 spacecraft

XSS-11's mission objective was to repeatedly demonstrate proximity operations using a microsatellite. The spacecraft was designed (with >600 m/s ∆V) to rendezvous with several resident space objects (including the upper stage of the Minotaur that inserted it into orbit) and to perform extended proximity operations including standoff inspection and both forced and natural circumnavigation. Key technologies to demonstrate included the proximity operation software and algorithms, small-aspect proximity sensors including the safety-critical MDA/Optech lidar, a highly-capable microsatellite bus with a modular payload interface, and TT&C techniques for proximity operations including collision safety and verification procedures. In addition to proving out AFRL’s technology goals, the flight demonstration of these rendezvous technologies was also needed to validate elements of NASA’s proposed plans to use spacecraft to collect samples of rocks and soil from Mars and return them to Earth for analysis.

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The RLS sensor measures the time of flight of a short duration (~1 ns) laser pulse which reflects off of a surface and returns to the sensor aperture. Using the speed of light, the time of flight is converted into the path length of the laser pulse, and hence, the range from the sensor to the surface can be measured. By steering the beam, the lidar is able to “paint” an object with laser pulses at high rate (~10 kHz) to create a three-dimensional image of the object. Depending upon the application, and the relative motion between the lidar and the object, a scan pattern can be specified to provide a dense or sparse image of the object.

Figure 2: XSS-11 Lidar Optical Head Unit (OHU) & Avionics Unit (AU) in the MDA sensor lab

The lidar hardware architecture consists of three items: the Optical Head Unit (OHU), the Avionics Unit (AU), and the cable harnesses connecting them. This architecture follows that used in the build-to-print space lidar design, shown in Figure 2.

3. ISS RENDEZVOUS, CAPTURE, AND BERTHING 3.1 Requirements Spacecraft that approach the ISS to berth or dock with the space station (termed ‘Visiting Vehicles’) have requirements placed on them by the Space Station Program. Those requirements that flow down to the rendezvous sensor suite on the visiting vehicle drive the function and performance of the sensors and decomposing these requirements to sensor system requirements is foundational to the development of pose measurement for the RLS. Figure 3 shows the key geometry for the approach and departure of a visiting vehicle. An interpretation of the critical zones is given below (Note that the trajectory shown in the diagram is for illustration purposes only). 3.1.1 Communication Sphere Typically, a visiting vehicle will establish two-way communications with the ISS before entering a 3-kilometer spherical region around the space station. Direct ranging to the station is preferred from this gate onwards, although differential absolute ranging methods have been proposed. Direct measurements of bearing are also useful throughout this region to improve the fidelity, and therefore the efficiency, of the approach maneuvers. 3.1.2 Approach Ellipsoid An Approach Ellipsoid (AE), which is a 4 km × 2 km × 2 km ellipsoid centered on the ISS’s center of mass, has been defined by NASA to assist in the specification of near-field rendezvous requirements. All 3σ trajectories, prior to the Approach Initiation (AI) burn maneuver that moves the visiting vehicle into the ellipsoid, must stay out of the AE for at least 24 hours.

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3.1.3 Keep-Out Sphere The Keep-Out Sphere (KOS) is a 200 meter radius sphere around the ISS. Within this 200-meter region, the vehicle must be within a predefined approach corridor. If the visiting vehicle leaves this approach corridor it must perform a separation maneuver to move outside the KOS.

Approach Ellipsoid (AE) .— Keep-out Sphere

3 Sigma Dispersion

(200m radius) Approach Initiation (AT)

3km radius spherical comm

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Ont of plane minor axis of AE is 2km

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Figure 3: ISS approach safety "gates"

The sensor system requirements are derived from these approach restrictions and from the control authority of the visiting vehicle itself. When a cargo vehicle approaches From 3 kilometers down to 100 meters, the sensor is required to provide range and bearing to the ISS. From 100 meters down to the capture zone, the sensor must provide range, bearing, and relative attitude information. Finally, as the vehicle prepares itself for capture, the sensor must provide relative rate information to assist in the zeroing of the relative vehicle drift rates to ensure a full capture window to the SSRMS operator.

Figure 4: Off-axis (slightly aft) R-bar view of ISS during STS-120 Figure 4 is a photograph of the space station approximating the horizontal field of view of the RLS at 400 meters range.

The actual function of the RLS with pose capability automatically acquires the pose of the ISS and provides full pose

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tracking starting at 400 meters. This is done to provide range and bearing to a specific reference frame on the station (e.g., the center of mass) without requiring any targets or retroreflectors to be visible; only the station geometry is needed. These high fidelity range & bearing measurements are provided down to 100 meters range where the relative orientations of the visiting vehicle and the ISS become important. Full relative pose is available to the GN&C right through to the capture region near the ISS Node 2. Once in the capture region, the sensor must provide rate measurements suited to zero the residual drift rates prior to SSRMS operations. Sensor system requirements include the time for initial target acquisition, time for subsequent target acquisitions (reacquisitions), relative vehicle rates for acquisition, range/bearing/pose update rate, worst case delay, pose resolution, pose rate resolution, translational/rotational pose accuracy, and translational/rotational pose rate accuracy.

4. SENSOR UPDATE RATE AND MEASUREMENT DELAY Sensor suite requirements are often formulated with accuracy and update rate requirements specified as a function of range-to-target. Operational dependencies and constraints aside, this leads to considerable confusion between passive full-frame imagers and active sequential point-by-point imagers as well as between those systems with closed-form vs. those with iterative signal processing algorithms. Typically, organizations that specify the accuracy and update rate requirements have made an implicit assumption that the measurement delay is no greater than the reciprocal of the update rate and that the measurement-by-measurement accuracy follows a Gaussian distribution. Comparing sensors that track this assumption with sensors that report root-mean-squared error or report an update rate that does not take into account frame-to-frame lag caused by an iterative data processing algorithm can be very difficult. It would be useful to have a standardized method for comparison that is tied more closely to the needs of the end users of these rendezvous sensors. It is illuminating to consider the spacecraft control requirement that drives the sensor requirement. The control system designer needs to be able to maneuver the spacecraft through certain trajectories. These trajectories have a frequency content; that is, the spacecraft must respond quickly enough to the control inputs so that its motion matches the desired trajectory (to within some threshold) in all positions and all angles. Any error that the sensor measures in that resulting trajectory will be fed back to the controller and will look like a trajectory error. Typically what a control system designer will do is ensure that the sensor that is specified can measure the frequencies of the trajectory much better than the spacecraft can perform those trajectories. A means which can be used to help with these analyses is a Bode plot; this plot shows the frequency response of a system to varying input frequencies in both magnitude and phase. If the bandwidth (the motion frequencies measured adequately both in amplitude and phase) of the sensor system is an order of magnitude higher than the bandwidth (the trajectory frequencies that can be tracked via maneuvers) of the spacecraft, the sensor system can be treated as providing a very nearly perfect measurement of the spacecraft motion. A plot of the frequency response of the sensor in magnitude, phase, and accuracy and the variation of these responses versus range-totarget allows for a complete and unambiguous specification of sensor performance independent of the type of sensor and provides the end user with a practical mathematical description of the sensor performance. A Bode plot can be generated for a 3-D pose sensor by oscillating the sensor with respect to a given target geometry across a spectrum of frequencies and comparing the magnitude and phase of the measurements against some ground truth. It is common for this type of sensor to behave nonlinearly, so a number of excitational amplitudes spanning the expected operational amplitudes should be used to characterize the frequency response of the sensor system. Presenting the specification of capabilities in the form of Bode plots and a steady-state accuracy plot permits the spacecraft control engineer to fully understand the operational characteristics of the sensor system. Furthermore, it also enables repeated and detailed simulations of spacecraft performance using the transfer function of the sensor system as a function of the relative trajectory.

5. POSE MEASUREMENT CAPABILITY Initial pose acquisition algorithms were developed and successfully tested under the operational constraints of the COTS mission to the ISS. The initial acquisition algorithm was demonstrated to be capable of providing robust pose acquisition at all extremes of the approach corridor. An optimal tracking algorithm was developed and successfully tested under the expected worst case spacecraft trajectories and motions starting from initial acquisition and operating right until capture. The tracking bandwidth and accuracy of the sensor was substantially increased without changing the sensor hardware. An overall verification plan was developed which efficiently combines simulation and selected

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hardware tests to verify the acquisition accuracy and robustness, re-acquisition accuracy and robustness, acquisition execution time, pose tracking convergence, tracking accuracy and robustness, and the pose bandwidth. The complete system was then integrated and successfully demonstrated using the engineering model RLS lidar sensor. The pose tracking development effort warrants particular consideration. The development of targetless pose capability in the existing flight lidar sensor required detailed mathematical analyses of all elements of the pose measurement in order to establish all the sufficient and necessary conditions for providing the functionality and performance required for the visiting vehicle spacecraft operations. In the process of performing these analyses, a number of tools were created to automate, or semi-automate, the validation of a solution given a specific target geometry. The tools developed address the following processes: 1. 2. 3. 4. 5. 6. 7.

Establish that a given 3D scene geometry has sufficient structure to measure relative pose. Find regions of the structure that, when sampled by the range sensor at 5 Hz, are the most favorable for measuring pose in terms of accuracy and robustness. Assist a systems engineer in the optimization of a scan pattern achievable within the power and controllability of the scanning lidar. Determine the minimum model representation resolution for modeling the geometry in memory. Generate a memory-optimal model representation of the client spacecraft geometry. Simulate, using a flight-equivalent-hardware-validated lidar simulator, the nominal and worst-case approaches and departures from any client spacecraft. Generate the Bode plot and accuracy plot given an approach trajectory.

These tools, and the demonstrations that were enabled by them, permitted the RLS development team to prove definitively that the flight-equivalent RLS with pose meets all the requirements for a primary visiting vehicle rendezvous sensor from far-range to capture.

Figure 5: Node 2 - Columbus interface from 25 m

By way of example, the process for validating that RLS with pose meets the requirements for a Commercial Orbital Transportation System (COTS) visiting vehicle involves a series of steps: 1.

Firstly, the geometry visible to the rendezvous sensor on the visiting vehicle is identified as a function of range. Figure 5 shows an example of the geometry visible to the lidar at a 25-meter range; the models are configuration-controlled CAD files administered by the ISS program.

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2.

A tool is then used to establish that all the scenes in the trajectory have sufficient structure to constrain all 6 degrees-of-freedom of pose. This same tool assesses which portions of the scenes provide maximal pose constraints when measured by the lidar at 5 Hz at the given range.

3.

With the preferred portions of the geometry, and another tool which aids the systems engineer in the selection of a scan pattern, a scan pattern is selected and scheduled into a flight parameters file to be used with a given scene for a span of ranges. The result is a system that will use the best scan pattern for a given scene and transition seamlessly as the scene changes as range decreases on approach and decreases during departure.

4.

A photographic verification step is used to ensure that the CAD models are consistent with the as-built modules. While the error budget includes allowance for variation between the CAD models and the as-built modules due to manufacturing tolerances and thermal expansion effects, it is important to also verify that no large structure has been added or scrubbed from the launch manifest and also to ascertain which components are obscured by cable harnesses or are protected by multi-layer insulation that is unmodeled in the CAD files. Figure 6 and Figure 7 show the two modules represented in Figure 5 as they are being delivered to the ISS for assembly. All the photographic evidence has shown that the CAD models are representative of the structures intended for use in pose measurement.

Figure 6: Close-up of Node 2 being delivered during Expedition 16 (STS-120)

5.

Model representations suitable for the degree of performance required at each given range are configured and automatically generated to support the approach trajectory. Several of these models can fit in memory simultaneously on the flight processor which minimizes the complexity of scheduling models and scan patterns as the rendezvous proceeds.

6.

A tool can then be used to produce Bode plats and measurement accuracy plots for each scenario of interest along the trajectory.

7.

With the optimum model representation in place and Bode plots demonstrating the required sensor performance, it becomes possible to simulate an entire approach (or departure) trajectory using a lidar simulator that has been validated with hardware testing.

8.

Ranges and scenes of particular interest can then be modeled as needed in hardware and demonstrated using a flight-equivalent RLS running pose on its flight processor.

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6. CONCLUSIONS The approach detailed above has yielded a high degree of confidence in the capability of using a single sensor to meet the requirements for rendezvous with the ISS and capture by the SSRMS. In particular, the resulting sensor system performance and functionality is fully compliant with the rendezvous and proximity operations sensor for the COTS mission. The principal innovative aspects of the technology that were developed in this program include: 1) efficacious algorithms to detect, recognize, and compute the pose of a client spacecraft from a single scan using an intelligent search of candidate solutions, 2) automatic scene evaluation and feature selection algorithms and software that assist mission planners in specifying accurate and robust scan scheduling, and 3) optimal pose tracking functionality using knowledge of the relative spacecraft states.

Figure 7: Columbus module in shuttle cargo bay awaiting deployment by the STS-122 crew

7. ACKNOWLEDGMENTS The authors wish to acknowledge their colleagues on the RLS with Pose development team: Catherine Erkorkmaz, Laurie Chappell, Derry Crymble, John Lymer, Craig Lyn, and Craig Rice at MDA. This work has been funded in part by the Canadian Space Agency’s Space Technology and Development Program.

8. REFERENCES [1] Nimelman, N., Tripp, J., Allen, A., Hiemstra, D.M., McDonald, S.A., “Spaceborne scanning lidar system (SSLS) upgrade path”, Proc. SPIE Vol. 6201, 62011V, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense V, May (2006) [2] Gregoris, D., Ulitsky, A., Vit, D.. Kerr, A., Dorcas, P., Bailak, G., Tripp, J., Gillett, R., Woodland, C., Richards, R., Sallaberger, C., “Laser imaging sensor system for on-orbit space shuttle inspection”, Proceedings of SPIE Spaceborne Sensors, Volume 5418, pages 61-68, (2004) [3] Pelletier, F., Golla, D., Allen, A., “Lidar-based Rendezvous Navigation for Mars Sample Return”, AIAA Astrodynamics Specialist Conference, Providence R.I., August (2004) [4] Allen, A., Mak, N., Langley, C., “Development of a Scaled Ground Testbed for Lidar-based Pose Estimation”, IEEE/RSJ IROS Workshop on Robot Vision for Space Applications, August (2005) [5] Lichti, D.D., “New Angular Resolution Measure for 3-D Laser Scanners”, Optical Engineering, 43(10): 2218-2219 (2004)

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