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.     

Planetary Rover Developments Supporting Mars Exploration, Sample Return and Future Human-Robotic Colonization

We overview our recent research on planetary mobility. Products of this effort include the Field Integrated Design & Operations rover (FIDO), Sample Return Rover (SRR), reconfigurable rover units that function as an All Terrain Explorer (ATE), and a multi-Robot Work Crew of closely cooperating rovers (RWC). FIDO rover is an advanced technology prototype; its design and field testing support NASA's development of long range, in situ Mars surface science missions. Complementing this, SRR implements autonomous visual recognition, navigation, rendezvous, and manipulation functions enabling small object pick-up, handling, and precision terminal docking to a Mars ascent vehicle for future Mars Sample Return. ATE implements on-board reconfiguration of rover geometry and control for adaptive response to adverse and changing terrain, e.g., traversal of steep, sandy slopes. RWC implements coordinated control of two rovers under closed loop kinematics and force constraints, e.g., transport of large payloads, as would occur in robotic colonies at future Mars outposts. RWC is based in a new extensible architecture for decentralized control of, and collective state estimation by multiple heterogeneous robotic platforms—CAMPOUT; we overview the key architectural features. We have conducted experiments with all these new rover system concepts over variable natural terrain. For each of the above developments, we summarize our approach, some of our key experimental results to date, and our future directions of planned development.     

Planetary Cliff Descent Using Cooperative Robots

Future robotic planetary exploration will need to traverse geographically diverse and challenging terrain. Cliffs, ravines, and fissures are of great scientific interest because they may contain important data regarding past water flow and past life.Highly sloped terrain is difficult and often impossible to safely navigate using a single robot. This paper describes a control system for a team of three robots that access cliff walls at inclines up to 70°. Two robot assistants, or anchors, lower a third robot, called the rappeller, down the cliff using tethers. The anchors use actively controlled winches to first assist the rappeller in navigation about the cliff face and then retreat to safe ground.This paper describes the coordination of these three robots so they function as a team to explore the cliff face. Stability requirements for safe operation are identified and a behavior-based control scheme is presented. Behaviors are defined for the system and command fusion methods are described. Controller stability and sensitivity are examined. System performance is evaluated with simulation, a laboratory system, and testing in field environments.     

Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers

Future planetary exploration missions will require wheeled mobile robots ("rovers") to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper, an online estimation method that identifies key terrain parameters using on-board robot sensors is presented. These parameters can be used for traversability prediction or in a traction control algorithm to improve robot mobility and to plan safe action plans for autonomous systems. Terrain parameters are also valuable indicators of planetary surface soil composition. The algorithm relies on a simplified form of classical terramechanics equations and uses a linear-least squares method to compute terrain parameters in real time. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for various soil types.     

An Architecture for Distributed Environment Sensing with Application to Robotic Cliff Exploration

Future planetary exploration missions will use cooperative robots to explore and sample rough terrain. To succeed robots will need to cooperatively acquire and share data. Here a cooperative multi-agent sensing architecture is presented and applied to the mapping of a cliff surface. This algorithm efficiently repositions the systems' sensing agents using an information theoretic approach and fuses sensory information using physical models to yield a geometrically consistent environment map. This map is then distributed among the agents using an information based relevant data reduction scheme. Experimental results for cliff face mapping using the JPL Sample Return Rover (SRR) are presented. The method is shown to significantly improve mapping efficiency over conventional methods.     

Decentralized Coordinated Tracking with Mixed Discrete–Continuous Decisions

In this paper, we study the problem of dynamically positioning a team of mobile robots for target tracking. We treat the coordination of mobile robots for target tracking as a joint team optimization to minimize uncertainty in target state estimates over a fixed horizon. The optimization is inherently a function of both the positioning of robots in continuous space and the assignment of robots to targets in discrete space. Thus, the robot team must make decisions over discrete and continuous variables. In contrast to methods that decouple target assignments and robot positioning, our approach avoids the strong assumption that a robot's utility for observing a target is independent of other robots’ observations. We formulate the optimization as a mixed integer nonlinear program and apply integer relaxation to develop an approximate solution in decentralized form. We demonstrate our coordinated multirobot tracking algorithm both in simulation and using a pair of mobile robotic sensor platforms to track moving pedestrians. Our results show that coupling target assignment and robot positioning realizes coordinated behaviors that are not possible with decoupled methods.     

Design of an autonomous agricultural robot

This paper presents a state-of-the-art review in the development of autonomous agricultural robots including guidance systems, greenhouse autonomous systems and fruit-harvesting robots. A general concept for a field crops robotic machine to selectively harvest easily bruised fruit and vegetables is designed. Future trends that must be pursued in order to make robots a viable option for agricultural operations are focused upon.A prototype machine which includes part of this design has been implemented for melon harvesting. The machine consists of a Cartesian manipulator mounted on a mobile chassis pulled by a tractor. Two vision sensors are used to locate the fruit and guide the robotic arm toward it. A gripper grasps the melon and detaches it from the vine. The real-time control hardware architecture consists of a blackboard system, with autonomous modules for sensing, planning and control connected through a PC bus. Approximately 85% of the fruit are successfully located and harvested.     

Controlling gaze with an embodied interactive control architecture

Human-Robot Interaction (HRI) is a growing field of research that targets the development of robots which are easy to operate, more engaging and more entertaining. Natural human-like behavior is considered by many researchers as an important target of HRI. Research in Human-Human communications revealed that gaze control is one of the major interactive behaviors used by humans in close encounters. Human-like gaze control is then one of the important behaviors that a robot should have in order to provide natural interactions with human partners. To develop human-like natural gaze control that can integrate easily with other behaviors of the robot, a flexible robotic architecture is needed. Most robotic architectures available were developed with autonomous robots in mind. Although robots developed for HRI are usually autonomous, their autonomy is combined with interactivity, which adds more challenges on the design of the robotic architectures supporting them. This paper reports the development and evaluation of two gaze controllers using a new cross-platform robotic architecture for HRI applications called EICA (The Embodied Interactive Control Architecture), that was designed to meet those challenges emphasizing how low level attention focusing and action integration are implemented. Evaluation of the gaze controllers revealed human-like behavior in terms of mutual attention, gaze toward partner, and mutual gaze. The paper also reports a novel Floating Point Genetic Algorithm (FPGA) for learning the parameters of various processes of the gaze controller.     

Global behavior via cooperative local control

The purpose of this paper is twofold. First, we outline important issues in designing real-time controllers for robots with numerous sensors, actuators, and behaviors. We address these issues by implementing a behavior based controller on a sophisticated autonomous robot. Hence, this work provides a point of reference for the scalability, ease of design, and effectiveness of the behavior based control for complex robots. Second, we explore the viability of using cooperation among local controllers to achieve coherent global behavior. Our approach is to decompose a difficult control task for a complex robot into a multitude of simpler control tasks for robotic subsystems. We illustrate and examine the effectiveness of this approach via rough terrain locomotion using an autonomous hexapod robot. Traversing rough terrain is a good task to test the viability of this approach because it requires a considerable amount of leg coordination. We found that implementing a complicated global control task with cooperating local controllers can effectively control complex robots.Support for this research was provided in part by a NASA Graduate Student Researcher Program Fellowship administered through the Jet Propulsion Laboratory, by Jet Propulsion Laboratory grant 959333, and by the Advanced Research Projects Agency under Office of Naval Research contract N00014-91-J-4038.     

Rule–based reasoning and neural network perception for safe off–road robot mobility

Operational safety and health monitoring are critical matters for autonomous field mobile robots such as planetary rovers operating on challenging terrain. This paper describes relevant rover safety and health issues and presents an approach to maintaining vehicle safety in a mobility and navigation context. The proposed rover safety module is composed of two distinct components: safe attitude (pitch and roll) management and safe traction management. Fuzzy logic approaches to reasoning about safe attitude and traction management are presented, wherein inertial sensing of safety status and vision–based neural network perception of terrain quality are used to infer safe speeds of traversal. Results of initial field tests and laboratory experiments are also described. The approach provides an intrinsic safety cognizance and a capacity for reactive mitigation of robot mobility and navigation risks.     

Experimental Testbed for Large Multirobot Teams

Experimental validation is particularly important in multi-robot systems research. The differences between models and real-world conditions that may not be apparent in single robot experiments are amplified because of the large number of robots, interactions between robots, and the effects of asynchronous and distributed control, sensing, and actuation. Over the last two years, we have developed an experimental testbed to support research in multirobot systems with the goal of making it easy for users to model, design, benchmark, and validate algorithms. In this article, we describe our approach to the design of a large-scale multirobot system for the experimental verification and validation of a variety of distributed robotic applications in an indoor environment.     

A formal framework for design and verification of robotic agents

Intelligent robots are autonomous and are used in environments where human interaction is hazardous or impossible. Verification of software for intelligent robots is mandatory because in situations where intelligent robots are employed online, error recovery is almost impossible. In this paper, we provide a formal framework for offline verification of software used in robotic applications. The specification enables one to design a robotic agent which represents a class of real-life robots. Forward and inverse kinematic operations of the robotic agent are specified using the specification for rigid solids and their primitive operations. An object-oriented design of the robotic agent derived from the specifications is given. We use the specification technique VDM for our purpose.This work was partially supported by FCAR, Quebec and NSERC, Canada.     

An Approach to the Development of Flexible Multirobot Systems: the Potential of Using Mobile Code Technology

Building multirobot systems exploiting mobile code technologies: this is quite an attractive possibility that, if successfully exploited, could very much improve the flexibility in development of systems composed of multiple mobile robots. In this paper we present two main contributions that constitute a significant step toward this ambitious scenario. In particular, we present architectural and technological solutions that enable both the mobility of code in a network of robots and the interfacing between robotic platforms and mobile code. Although we are aware that the results presented in this paper are still preliminary and limited, we demonstrate their promising potential with experiments involving two mobile robots.     

Biologically Inspired Behaviour Design for Autonomous Robotic Fish

Behaviour-based approach plays a key role for mobile robots to operate safely in unknown or dynamically changing environments. We have developed a hybrid control architecture for our autonomous robotic fish that consists of three layers: cognitive, behaviour and swim pattern. In this paper, we describe some main design issues of the behaviour layer, which is the centre of the layered control architecture of our robotic fish. Fuzzy logic control (FLC) is adopted here to design individual behaviours. Simulation and real experiments are presented to show the feasibility and the performance of the designed behaviour layer.     

高精度激光测距下的机器人自主避障控制

在机器人自主避障过程中,由于传感器数据的误差会降低机器人感知和决策的准确性,从而影响机器人自主避障能力。为此,提出高精度激光测距下的机器人自主避障控制方法。通过设计机器人体系结构,建立机器人运动学模型,为机器人避障控制提供依据。采用高精度激光测距技术,构建机器人移动场地地形。通过自适应阈值方法,完成机器人的自主避障控制。实验结果表明,所提方法的机器人自主避障控制效果好,且障碍物位置测试值与实际位置值的误差保持在0.5m以内,具有较高的避障控制精确度。     

A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots

Autonomous mobile robots navigating in changing and dynamic unstructured environments like the outdoor environments need to cope with large amounts of uncertainties that are inherent of natural environments. The traditional type-1 fuzzy logic controller (FLC) using precise type-1 fuzzy sets cannot fully handle such uncertainties. A type-2 FLC using type-2 fuzzy sets can handle such uncertainties to produce a better performance. In this paper, we present a novel reactive control architecture for autonomous mobile robots that is based on type-2 FLC to implement the basic navigation behaviors and the coordination between these behaviors to produce a type-2 hierarchical FLC. In our experiments, we implemented this type-2 architecture in different types of mobile robots navigating in indoor and outdoor unstructured and challenging environments. The type-2-based control system dealt with the uncertainties facing mobile robots in unstructured environments and resulted in a very good performance that outperformed the type-1-based control system while achieving a significant rule reduction compared to the type-1 system.     

Rough Terrain Autonomous Mobility—Part 2: An Active Vision, Predictive Control Approach

Off-road autonomous navigation is one of the most difficult automation challenges from the point of view of constraints on mobility, speed of motion, lack of environmental structure, density of hazards, and typical lack of prior information. This paper describes an autonomous navigation software system for outdoor vehicles which includes perception, mapping, obstacle detection and avoidance, and goal seeking. It has been used on several vehicle testbeds including autonomous HMMWV's and planetary rover prototypes. To date, it has achieved speeds of 15 km/hr and excursions of 15 km.We introduce algorithms for optimal processing and computational stabilization of range imagery for terrain mapping purposes. We formulate the problem of trajectory generation as one of predictive control searching trajectories expressed in command space. We also formulate the problem of goal arbitration in local autonomous mobility as an optimal control problem. We emphasize the modeling of vehicles in state space form. The resulting high fidelity models stabilize coordinated control of a high speed vehicle for both obstacle avoidance and goal seeking purposes. An intermediate predictive control layer is introduced between the typical high-level strategic or artificial intelligence layer and the typical low-level servo control layer. This layer incorporates some deliberation, and some environmental mapping as do deliberative AI planners, yet it also emphasizes the real-time aspects of the problem as do minimalist reactive architectures.     

Multirobot inspection of industrial machinery

Inspection of aircraft and power generation machinery using a swarm of miniature robots is a promising application both from an intellectual and a commercial perspective. Our research is motivated by a case study concerned with the inspection of a jet turbine engine by a swarm of miniature robots. This article summarizes our efforts that include multirobot path planning, modeling of self-organized robotic systems, and the implementation of proof-of-concept experiments with real miniature robots. Although other research tackles challenges that arise from moving within three-dimensional (3-D) structured environments at the level of the individual robotic node, the emphasis of our work is on explicitly incorporating the potential limitations of the individual robotic platform in terms of sensor and actuator noise into the modeling and design process of collaborative inspection systems. We highlight difficulties and further challenges on the (lengthy) path toward truly autonomous parallel robotic inspection of complex engineered structures.     

A Prey Catching and Predator Avoidance Neural-Schema Architecture for Single and Multiple Robots

The paper presents a biologically inspired multi-level neural-schema architecture for prey catching and predator avoidance in single and multiple autonomous robotic systems. The architecture is inspired on anuran (frogs and toads) neuroethological studies and wolf pack group behaviors. The single robot architecture exploits visuomotor coordination models developed to explain anuran behavior in the presence of preys and predators. The multiple robot architecture extends the individual prey catching and predator avoidance model to experiment with group behavior. The robotic modeling architecture distinguishes between higher-level schemas representing behavior and lower-level neural structures representing brain regions. We present results from single and multiple robot experiments developed using the NSL/ASL/MIRO system and Sony AIBO ERS-210 robots.     

A fail-safe tele-autonomous robotic system for nuclear facilities

A fail-safe tele-autonomous robotic system is proposed for use in advanced nuclear reprocessing facilities. The design exploits the technologies developed for space telerobotics. The target system consists of a graphical user interface for an operator to execute robotic tasks, hand controllers for teleoperation, a three-dimensional graphical simulator, and robot control software to drive both the graphical simulation and dual six degree-of-freedom robots to perform tasks using autonomous, teleoperated, and shared control modes. A preliminary design for a safety monitoring system for fail-safe operations is also described.