Reactive navigation in outdoor environments using potential fields

Haddad, Hassan; Khatib, Maher; Lacroix, Simon; Chatila, Raja

doi:10.1109/robot.1998.677268

Cited by 90 publications

(44 citation statements)

References 7 publications

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“…I X T E T decides when to start or stop an action in the plan and handles plan adaptations. OpenPRS expands the action into commands to the functional level 11 , monitors its execution and can recover from specific failures. It finally reports to I X T E T upon the action completion.…”

Section: Experimentation and Resultsmentioning

confidence: 99%

“…b) Path generation: On the basis of this probabilistic obstacle representation, various ways to find paths can be applied. In previous work, we proposed a potential-field based approach [11], however approaches that evaluate a set of elementary trajectories (figure 5), similarly to the Morphin algorithm [12], proved to yield better results.…”

Section: B Flat Terrain Navigation Modesmentioning

confidence: 99%

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Decisional autonomy of planetary rovers

Ingrand

Lacroix

Lemai-Chenevier

et al. 2007

Journal of Field Robotics

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To achieve the ever increasing demand for science return, planetary exploration rovers require more autonomy to successfully perform their missions. Indeed, the communication delays are such that teleoperation is unrealistic. Although the current rovers (such as MER) demonstrate a limited navigation autonomy, and mostly rely on ground mission planning, the next generation (e.g. NASA Mars Science Laboratory and ESA Exomars) will have to regularly achieve long range autonomous navigation tasks.However, fully autonomous long range navigation in partially known planetary-like terrains is still an open challenge for robotics. Navigating hundreds of meters without any human intervention requires the robot to be able to build adequate representations of its environment, to plan and execute trajectories according to the kind of terrain traversed, to control its motions and to localize itself as it moves.All these activities have to be planned, scheduled, and performed according to the rover context, and controlled so that the mission is correctly fulfilled. To achieve these objectives, we have developed a temporal planner and an execution controller, that exhibit plan repair and replanning capabilities. The planner is in charge of producing plans composed of actions for navigation, science activities (moving and operating instruments), communication with Earth and with an orbiter or a lander, while managing resources (power, memory, etc) and respecting temporal constraints (communication visibility windows, rendezvous, etc). High level actions also need to be refined and their execution temporally and logically controlled. Last, in such critical applications, we believe it is important to deploy a component which protects the system against dangerous or even fatal situations resulting from unexpected interactions between subsystems (e.g. move the robot while the robot arm is unstowed) and/or software components (e.g. take and store a picture in a buffer while the previous one is still being processed).In this article we review the aforementioned capabilities, that have been developed, tested and evaluated on board our rovers (Lama and Dala). After an overview of the architecture design principle adopted, we summarize the perception, localization and motion generation capabilities -required by autonomous navigation -and their integration and concurrent operation in a global architecture. We then detail the decisional components : a high level temporal planner which produces the robot activity plan on board, and temporal and procedural execution controllers. We show how some failures or execution delays are being taken care of with online local repair, or replanning.

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Section: Experimentation and Resultsmentioning

confidence: 99%

Section: B Flat Terrain Navigation Modesmentioning

confidence: 99%

Decisional autonomy of planetary rovers

Ingrand

Lacroix

Lemai-Chenevier

et al. 2007

Journal of Field Robotics

View full text Add to dashboard Cite

show abstract

“…Thus, the system has been used on other robots [55], including two indoor and one outdoor scenarios at the LAAS-CNRS, France; one indoor in the Technical University of Lisbon, Portugal; and two indoor in the University of Zaragoza, Spain. In these cases, the modeling module was replaced by modules to process a 3D laser, ultrasounds following [35], or a pair of cameras [56].…”

Section: Discussionmentioning

confidence: 99%

Sensor-based robot motion generation in unknown, dynamic and troublesome scenarios

Mínguez

Montano

2005

Robotics and Autonomous Systems

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A sensor-based motion control system was designed to autonomously drive vehicles free of collisions in unknown, troublesome and dynamic scenarios. The system was developed based on a hybrid architecture with three layers (modeling, planning and reaction). The interaction of the modules was based on a synchronous planner-reactor configuration where the planner computes tactical information to direct the reactivity. Our system differs from previous ones in terms of the choice of the techniques implemented in the modules and in the integration architecture. It can achieve robust and reliable navigation in difficult scenarios that are troublesome for many existing methods. Experiments carried out in these scenarios with a real vehicle confirm the effectiveness of this technique.

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“…These approaches have been widely applied to path planning of a mobile robot and a manipulator (Borenstein and Koren, 1989;Chuang, 1998;Chuang and Ahuja, 1998;Chuang et al, 2000;Guldner and Utkin, 1995;Haddad et al, 1998;Hwang and Ahuja, 1992;Tsai et al, 2001;Vadakkepat, 2001;Veelaert and Bogaerts, 1999). The applications of artificial potential field for obstacle avoidance was first developed by Khatib (Khatib, 1985;Khatib, 1986).…”

Section: Itroductionmentioning

confidence: 99%

Real-Time Path Planning in Unknown Environments Using a Virtual Hill

Park

Lee

2005

IFAC Proceedings Volumes

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The artificial potential field based path planning has been most wisely used for local path planning because it provides simple and efficient motion planners for practical purposes. However, this approach has a local minimum problem which can trap a robot before reaching its goal. The local minimum problem is sometimes inevitable when a mobile robot moves in unknown environments, because the robot cannot predict local minima before it detects obstacles forming the local minima. The avoidance of local minima has been an active research topic in the potential field based path planning. In this study, we propose a new concept using a virtual hill to escape local minima that occur in local path planning for a mobile robot. A virtual hill is located around local minimum to repel a robot from local minimum. Copyright © 2005 IFAC Keywords: mobile robot, path planning, artificial potential field, virtual hill, extra potential, navigation. ITRODUCTIONArtificial potential field methods provide simple and effective motion planners for practical purposes (Lee and Park, 1991). These approaches have been widely applied to path planning of a mobile robot and a manipulator (Borenstein and Koren, 1989;Chuang, 1998;Chuang and Ahuja, 1998;Chuang et al., 2000;Guldner and Utkin, 1995;Haddad et al., 1998;Hwang and Ahuja, 1992;Tsai et al, 2001;Vadakkepat, 2001;Veelaert and Bogaerts, 1999). The applications of artificial potential field for obstacle avoidance was first developed by Khatib (Khatib, 1985;Khatib, 1986). This approach uses two types of potential, which are a repulsive potential field to force a robot away from obstacles or forbidden regions and an attractive potential field to drive the robot to its goal. The robot moves under the action of the artificial force which is proportional to the negative gradient of artificial potential. The robot is driven from the positions with the higher potential to that with the lower potential.However, the path planning by the artificial potential field approach has a major problem, a local minimum problem, which can trap a robot before reaching its goal. The local minimum problem is sometimes unavoidable in local path planning, because the robot can detect only local information on obstacles. In other words, the robot cannot predict local minima before experiencing the environment. An avoidance of a local minimum has been an active research topic in potential field based path planning (Chang, 1996;Cho and Kwon, 1996;Connolly et al., 1990; Connolly, 1992;Janabi-Sharifi and Vinke, 1993;Kim and Khosla, 1992; Lee and Park, 1991;McFetridge and Yousef-Ibrahim, 1998;Park and Lee, 2003; Rimom and Koditschek, 1992;Volpe and Khosla, 1990). However, the previous solutions were limited to simple formations of obstacles or available for path planning in known environments.

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Reactive navigation in outdoor environments using potential fields

Cited by 90 publications

References 7 publications

Decisional autonomy of planetary rovers

Decisional autonomy of planetary rovers

Sensor-based robot motion generation in unknown, dynamic and troublesome scenarios

Real-Time Path Planning in Unknown Environments Using a Virtual Hill

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