Hrand Aghazarian

CAMPOUT: a control architecture for tightly coupled coordination of multirobot systems for planetary surface exploration

Exploration of high risk terrain areas such as cliff faces and site construction operations by autonomous robotic systems on Mars requires a control architecture that is able to autonomously adapt to uncertainties in knowledge of the environment. We report on the development of a software/hardware framework for cooperating multiple robots performing such tightly coordinated tasks. This work builds on our earlier research into autonomous planetary rovers and robot arms. Here, we seek to closely coordinate the mobility and manipulation of multiple robots to perform examples of a cliff traverse for science data acquisition, and site construction operations including grasping, hoisting, and transport of extended objects such as large array sensors over natural, unpredictable terrain. In support of this work we have developed an enabling distributed control architecture called control architecture for multirobot planetary outposts (CAMPOUT) wherein integrated multirobot mobility and control mechanisms are derived as group compositions and coordination of more basic behaviors under a task-level multiagent planner. CAMPOUT includes the necessary group behaviors and communication mechanisms for coordinated/cooperative control of heterogeneous robotic platforms. In this paper, we describe CAMPOUT, and its application to ongoing physical experiments with multirobot systems at the Jet Propulsion Laboratory in Pasadena, CA, for exploration of cliff faces and deployment of extended payloads.

Mars rover pair cooperatively transporting a long payload

The objective of the Robot Work Crew (RWC) project is to investigate key challenges in multi-robot coordination when performing tightly coupled coordination tasks such as transporting and handling of long objects on challenging planetary terrain. In this paper, we focus on tightly coupled coordination of two Mars rovers transporting a long payload. We have developed practical decentralized compliancy control and coordinated comply control algorithms that effectively address compliant control for compliantly coupled multiple mobile robots. Experiments at the Jet Propulsion Lab in Pasadena, CA of two Mars rovers carry an extended payload over uneven, natural terrain are used to validate and illustrate the approach.

Rover autonomy for long range navigation and science data acquisition on planetary surfaces

This paper describes recent work undertaken at the Jet Propulsion Laboratory in Pasadena, CA in the area of increased rover autonomy for planetary surface operations. The primary vehicle for this work is the Field Integrated, Design and Operations (FIDO) rover. The FIDO rover is an advanced technology prototype that is a terrestrial analog of the Mars Exploration Rovers (MER) being sent to Mars in 2003. We address the autonomy issue through improved integration of rover based sensing and higher level onboard planning capabilities. The sensors. include an inertial navigation unit (INU) with 3D gyros and accelerometers, a sun sensor, mast and body mounted imagery, and wheel encoders. Multisensor fusion using an Extended Kalman Filter (EKF) approach coupled with pattern recognition and tracking algorithms has enabled the autonomy that is necessary for maximizing science data return while minimizing the number of ground loop interactions. These algorithms are coupled with a long range navigation algorithm called ROAMAN (Road Map Navigation) for an integrated approach to rover autonomy. We also report the results of algorithm validation studies in remote field trials at Black Rock Summit in Central Nevada, Californias Mojave Desert, and the Arroyo Seco at JPL.

Stereo vision–based navigation for autonomous surface vessels

This paper describes a stereo vision–based system for autonomous navigation in maritime environments. The system consists of two key components. The Hammerhead vision system detects geometric hazards (i.e., objects above the waterline) and generates both grid-based hazard maps and discrete contact lists (objects with position and velocity). The R4SA (robust, real-time, reconfigurable, robotic system architecture) control system uses these inputs to implement sensor-based navigation behaviors, including static obstacle avoidance and dynamic target following. As far as the published literature is concerned, this stereo vision–based system is the first fielded system that is tailored for high-speed, autonomous maritime operation on smaller boats. In this paper, we present a description and experimental analysis of the Hammerhead vision system, along with key elements of the R4SA control system. We describe the integration of these systems onto a number of high-speed unmanned surface vessels and present experimental results for the combined vision-based navigation system.

Free-Climbing with a Multi-Use Robot

This paper presents a new four-limbed robot, LEMUR IIb (Legged Excursion Mechanical Utility Rover), that can free-climb vertical rock surfaces. This robot was designed to have a number of capabilities in addition to climbing (e.g., assembly, inspection, maintenance, transport, intervention) and to be able to traverse a variety of other types of terrain (e.g., roads, talus, dirt, urban rubble). To maximize its flexibility in this regard, LEMUR IIb will need to exploit sophisticated control, planning, and sensing techniques in order to climb, rather than rely on specific hardware modifications. In particular, this paper describes a new algorithm for planning safe one-step climbing moves, which has already enabled LEMUR IIb to climb an indoor, near-vertical surface with small, arbitrarily distributed, natural features. To the authors’ knowledge, this is the first experimental demonstration of a multi-use, multi-limbed robot climbing such terrain using only friction at contact points (i.e., free-climbing).

Reconfigurable robots for all-terrain exploration

While significant recent progress has been made in development of mobile robots for planetary surface exploration, there remain major challenges. These include increased autonomy of operation, traverse of challenging terrain, and fault-tolerance under long, unattended periods of use. We have begun work which addresses some of these issues, with an initial focus on problems of high risk access, that is, autonomous roving over highly variable, rough terrain. This is a dual problem of sensing those conditions which require rover adaptation, and controlling the rover actions so as to implement this adaptation in a well understood way (relative to metrics of rover stability, traction, power utilization, etc.). Our work progresses along several related technical lines: 1) development a fused state estimator which robustly integrates internal rover state and externally sensed environmental information to provide accurate configuration information; 2) kinematic and dynamical stability analysis of such configurations so as to determine predicts for a needed change of control regime (e.g., traction control, active c.g. positioning, rover shoulder stance/pose); 3) definition and implementation of a behavior-based control architecture and action-selection strategy which autonomously sequences multi-level rover controls and reconfiguration. We report on these developments, both software simulations and hardware experimentation. Experiments include reconfigurable control of JPSs Sample Return Rover geometry and motion during its autonomous traverse over simulated Mars terrain.

Rover localization results for the FIDO rover

This paper describes the development of a two-tier state estimation approach for NASA/JPLs FIDO Rover that utilizes wheel odometry, inertial measurement sensors, and a sun sensor to generate accurate estimates of the rovers position and attitude throughout a rover traverse. The state estimation approach makes use of a linear Kalman filter to estimate the rate sensor bias terms associated with the inertial measurement sensors and then uses these estimated rate sensor bias terms to compute the attitude of the rover during a traverse. The estimated attitude terms are then combined with the wheel odometry to determine the rovers position and attitude through an extended Kalman filter approach. Finally, the absolute heading of the vehicle is determined via a sun sensor which is then utilized to initialize the rovers heading prior to the next planning cycle for the rovers operations. This paper describes the formulation, implementation, and results associated with the two-tier state estimation approach for the FIDO rover.

Distributed Control of Multi-Robot Systems Engaged in Tightly Coupled Tasks

NASA mission concepts for the upcoming decades of this century include exploration of sites such as steep cliff faces on Mars, as well as infrastructure deployment for a sustained robotic/manned presence on planetary and/or the lunar surface. Single robotic platforms, such as the Sojourner rover successfully flown in 1997 and the Mars Exploration Rovers (MER) which landed on Mars in January of 2004, have neither the autonomy, mobility, nor manipulation capabilities for such ambitious undertakings. One possible approach to these future missions is the fielding of cooperative multi-robot systems that have the required onboard control algorithms to more or less autonomously perform tightly coordinated tasks. These control algorithms must operate under the constrained mass, volume, processing, and communication conditions that are present on NASA planetary surface rover systems. In this paper, we describe the design and implementation of distributed control algorithms that build on our earlier development of an enabling architecture called CAMPOUT (Control Architecture for Multi-robot Planetary Outposts). We also report on some ongoing physical experiments in tightly coupled distributed control at the Jet Propulsion Lab in Pasadena, CA where in the first study two rovers acquire and carry an extended payload over uneven, natural terrain, and in the second three rovers form a team for cliff access.

Lemur IIb: a Robotic System for Steep Terrain Access

Purpose – Introduces the Lemur IIb robot which allows the investigation of the technical hurdles associated with free climbing in steep terrain. These include controlling the distribution of contact forces during motion to ensure holds remain intact and to enable mobility through over‐hangs. Efforts also can be applied to further in‐situ characterization of the terrain, such as testing the strength of the holds and developing models of the individual holds and a terrain map.Design/methodology/approach – A free climbing robot system was designed and integrated. Climbing end‐effector were investigated and operational algorithms were developed.Findings – A 4‐limbed robotic system used to investigate several aspects of climbing system design including the mechanical system (novel end‐effectors, kinematics, joint design), sensing (force, attitude, vision), low‐level control (force‐control for tactile sensing and stability management), and planning (joint trajectories for stability). A new class of Ultrasonic/S...

Sustainable cooperative robotic technologies for human and robotic outpost infrastructure construction and maintenance

Robotic Construction Crew (RCC) is a heterogeneous multi-robot system for autonomous acquisition, transport, and precision mating of components in construction tasks. RCC minimizes use of resources constrained by a space environment such as computation, power, communication, and sensing. A behavior-based architecture provides adaptability and robustness despite low computational requirements. RCC successfully performs several construction related tasks in an emulated outdoor environment despite high levels of uncertainty in motions and sensing. This paper provides quantitative results for formation keeping in component transport, precision instrument placement, and construction tasks.