{"project":{"acronym":"","projectId":91549,"title":"Reducing Risk and Increasing Exploration Payoff with Symbiotic Rover Pairs","primaryTaxonomyNodes":[{"taxonomyNodeId":10605,"taxonomyRootId":8816,"parentNodeId":10604,"level":3,"code":"TX03.3.1","title":"Management and Control","definition":"Management and control includes the control algorithms, models, and sensors needed to control a spacecraft, rover, probes, aircraft power bus, or other vehicles, to include fault detection, isolation, and recovery.","exampleTechnologies":"Autonomous fault detection, isolation, and recovery (FDIR) algorithms and technologies for complex power systems, hierarchical and distributed control of a power system, power source and energy storage control, real-time power system simulation","hasChildren":false,"hasInteriorContent":true}],"startTrl":2,"currentTrl":3,"endTrl":3,"benefits":"The proposed research will allow symbiotic rover teams to better navigate and explore hazardous terrain by developing and applying innovative methods in combined path planning, task allocation, and localization. The algorithms developed by this research will enable symbiotic rovers to boldly explore scientific frontiers currently considered beyond-limits by NASA.","description":"Planetary explorations missions avoid the destinations that offer the greatest scientific payout because these destinations come with a risk too great for a primary rover. The many caves, canyons, and pits that cover the surface of Mars and the Moon have immense scientific value, yet the rugged terrain and precipitous slopes of these features are too dangerous to risk the primary mission asset. The solution to this risk problem is a symbiotic architecture consisting of a primary rover and one or more secondary companion rovers. These secondary rovers would be less expensive, potentially expendable, and capable of exploring hazardous terrain and features without risking the mission if lost. The benefits of a symbiotic architecture extend far beyond simple risk mitigation - the secondary rovers could explore more area efficiently, provide operators with additional viewpoints of objects of interest, and assist operators in debugging problems with the primary rover by providing views that would be otherwise impossible to take. Though symbiotic multi-robot systems have been developed, few have been in the context of hazardous planetary exploration. Those that have, focus primarily on the mechanical challenges of such a system. There are multiple algorithmic challenges relating to coordination between the rovers that are barriers to a symbiotic rover architecture being realized. The proposed research will allow symbiotic rover teams to better navigate and explore hazardous terrain by developing and applying innovative methods in combined path planning, task allocation, and localization. The algorithms developed by this research will enable symbiotic rovers to boldly explore scientific frontiers currently considered beyond-limits by NASA. The proposed research will improve current distance and time constrained multi-robot path planning algorithms by shifting the constraints from the time domain to resource cost domain. This will allow the secondary rover with more limited resources (energy, sample storage, etc.) to rendezvous with the primary rover before the resource is expended. Initial experimentation of the algorithm will be done in simulation by automatically generating the hazard maps and verifying the optimality of the generated paths. If they are consistently successful, the methods and algorithms will be tested in the field with mobile robots. Improved task allocation methods are necessary if the primary and secondary rovers are to best assign waypoints according to their capabilities and constraints. By modeling the challenge of waypoint allocation as one of distributed constraint optimization (DCOP) and combining it with the resource-based path planning discussed above, better allocation of waypoints will be achieved. As the task allocation algorithm is tightly coupled with the path planner, it will be developed and tested in conjunction with it by verifying whether or not the waypoints the rovers choose to travel are optimal given the rovers capabilities. The secondary rover's smaller size and lower processing power may preclude methods of localization currently used by most rovers. This research will investigate methods of localizing the secondary rover absolutely by determining an accurate relative localization to the primary rover, which does not have the same constraints. Initial testing of the algorithm will use sensors analogous to those the secondary rover would have available. A radio time-distance-of-arrival sensor will be used to determine the distance between the primary rover and secondary rover and a sun sensor will be used to determine absolute orientation. By taking successive readings of these sensors and comparing them to the known location of the primary rover, an accurate absolute localization of the secondary rover can be achieved.","startYear":2015,"startMonth":8,"endYear":2016,"endMonth":5,"statusDescription":"Completed","principalInvestigators":[{"contactId":497355,"canUserEdit":false,"firstName":"William","lastName":"Whittaker","fullName":"William Whittaker","fullNameInverted":"Whittaker, William","primaryEmail":"red@cmu.edu","publicEmail":false,"nacontact":false}],"programDirectors":[{"contactId":84634,"canUserEdit":false,"firstName":"Claudia","lastName":"Meyer","fullName":"Claudia M Meyer","fullNameInverted":"Meyer, Claudia M","middleInitial":"M","primaryEmail":"claudia.m.meyer@nasa.gov","publicEmail":true,"nacontact":false}],"programExecutives":[{"contactId":84634,"canUserEdit":false,"firstName":"Claudia","lastName":"Meyer","fullName":"Claudia M Meyer","fullNameInverted":"Meyer, Claudia M","middleInitial":"M","primaryEmail":"claudia.m.meyer@nasa.gov","publicEmail":true,"nacontact":false}],"programManagers":[{"contactId":183514,"canUserEdit":false,"firstName":"Hung","lastName":"Nguyen","fullName":"Hung D Nguyen","fullNameInverted":"Nguyen, Hung D","middleInitial":"D","primaryEmail":"hung.d.nguyen@nasa.gov","publicEmail":true,"nacontact":false}],"projectManagers":[{"contactId":319297,"canUserEdit":false,"firstName":"Masahiro","lastName":"Ono","fullName":"Masahiro Ono","fullNameInverted":"Ono, Masahiro","primaryEmail":"masahiro.ono@jpl.nasa.gov","publicEmail":true,"nacontact":false}],"coInvestigators":[{"contactId":244332,"canUserEdit":false,"firstName":"Joseph","lastName":"Amato","fullName":"Joseph L Amato","fullNameInverted":"Amato, Joseph L","middleInitial":"L","primaryEmail":"jamato@andrew.cmu.edu","publicEmail":false,"nacontact":false}],"website":"https://www.nasa.gov/directorates/spacetech/home/index.html","libraryItems":[],"transitions":[{"transitionId":75844,"projectId":91549,"transitionDate":"2016-05-01","path":"Closed Out","details":"The planetary regions that offer the greatest scientific value are often also the riskiest to explore. The caves and canyons covering the surface of the Moon present safe havens from radiation and micrometeorites. The craters on the Lunar poles show promise for harboring volatiles such as water and hydrogen. Recurring slope linea on the steep cliffs of Mars may contain evidence of past life. All of these are prime locations for future missions, but contain a significant amount of risk during their exploration. Much of this risk stems from the current approach of sending a single rover as the sole mobile mission asset to explore these regions. The Planetary Robotics Laboratory at Carnegie Mellon University has proposed the idea that Symbiotic Exploration, multiple rovers complimenting each other's strengths and weaknesses will be far more effective at exploring these regions while significantly mitigating the risk that comes from single-rover architectures. Multiple rovers allows missions to explore more area, take greater risks, and reap better rewards. While the mechanical challenges of Symbiotic Exploration has been studied through such rovers as JPL's Axel and the Tokyo Institute of Technologies SMC Rover, the algorithmic challenges have been less thoroughly explored, specifically with regards to symbiotic path planning. These challenges include resource constrained planning for operating in light and power sparse environments, multi-agent resourcebased rendezvous for dropping off samples and recharging power, and maximum separation distance during routes to enable constant communication between rovers. This research sought to develop a multi-rover path planner capable of generating routes for multiple heterogeneous rovers that address the above constraints inherent in symbiotic exploration. To do this, an iterative multi-rover path planning algorithm known as Distributed Path Consensus (DPC) was adapted to handle symbiotic constraints. The core idea behind DPC is to first plan unconstrained paths for each rover to their goals, and then make slight adjustments to these paths through a weighted penalty function that draws the rovers closer together at desired points in time. A key challenge with DPC is that it is only able to enforce constraints based upon a known point in time. In the case of a rover expending energy, the moment in time when it will require recharging is not known. Furthermore the value at which the constraint is applied must be identical across both rovers. There is no way of having the robots rendezvous when one of them has expended a certain amount of energy, regardless of when or where that occurs. This research proposed an enhancement to the DPC algorithm (known as DPC.TF) to address these shortcomings. This was done through the definition of two classes of constraints: Feeder constraints that apply when a certain condition is met for a rover (eg. it has traveled 30 meters or has expended 1 kWh of energy); and Tanker constraints that apply when the partner's constraint is met. Through these two classes of constraints rendezvous based upon resource expenditure, as well as maintaining communication distance between two rovers can be enforced. DPC.TF allows for complex constraints between multiple rovers could be easily specified to allow rovers to plan paths to different goals while rendezvousing to replenish battery levels, drop of samples, and communicate data. This capability presents a major upgrade from the state of the art DPC algorithm which only allowed for rendezvous between rovers at predetermined times, rather than dynamically based upon research expenditure. This algorithm, and its corresponding planner, were used to show that routes on the Lunar south pole do exist that could be used to explore the permanently shadowed regions most likely to harbor volatiles. ","infoText":"Closed out","infoTextExtra":"","dateText":"May 2016"}],"responsibleMd":{"acronym":"STMD","canUserEdit":false,"city":"","external":false,"linkCount":0,"organizationId":4875,"organizationName":"Space Technology Mission Directorate","organizationType":"NASA_Mission_Directorate","naorganization":false,"organizationTypePretty":"NASA Mission Directorate"},"program":{"acronym":"STRG","active":true,"description":"
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