Nearness diagram navigation (ND): a new real time collision avoidance approach

Mínguez, Javier; Montano, Luis

doi:10.1109/iros.2000.895280

Cited by 81 publications

(49 citation statements)

References 14 publications

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“…Prior Work on Obstacle Avoidance : Local reactive obstacle avoidance techniques [1,2,3] have been quite popular due to their simplicity and fast computation. Some works [2,3], utilize the natural robot-centric polar frame to choose the best direction to move.…”

Section: Introductionmentioning

confidence: 99%

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A Simple Reactive Obstacle Avoidance Algorithm and Its Application in Singapore Harbor

Bandyophadyay

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2010

Springer Tracts in Advanced Robotics

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Autonomous surface craft (ASC) are increasingly attractive as a means for performing harbor operations including monitoring and inspection. However, due to the presence of many fixed and moving structures such as pilings, moorings, and vessels, harbor environments are extremely dynamic and cluttered. In order to move autonomously in such conditions ASC's must be capable of detecting stationary and moving objects and plan their paths accordingly. We propose a simple and scalable online navigation scheme, wherein the relative motion of surrounding obstacles is estimated by the ASC, and the motion plan is modified accordingly at each time step. Since the approach is model-free and its decisions are made at a high frequency, the system is able to deal with highly dynamic scenarios. We deployed ASC's in the Selat Pauh region of Singapore Harbor to test the technique using a short-range 2-D laser sensor; detection in the rough waters we encountered was quite poor. Nonetheless, the ASC's were able to avoid both stationary as well as mobile obstacles, the motions of which were unknown a priori. The successful demonstration of obstacle avoidance in the field validates our fast online approach.

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Section: Introductionmentioning

confidence: 99%

“…Some works [2,3], utilize the natural robot-centric polar frame to choose the best direction to move. While these algorithms plan in position space, others [11,4] map the obstacles in the velocity space and choose suitable control parameters to satisfy kinematic constraints.…”

Section: Introductionmentioning

confidence: 99%

A Simple Reactive Obstacle Avoidance Algorithm and Its Application in Singapore Harbor

Bandyophadyay

Sarcione

Hover

2010

Springer Tracts in Advanced Robotics

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“…In [11] the concept of the nearness diagram is presented identifying five different navigation laws according to a robot security measure. In choosing different motion commands for each of the five cases, a simple reasoning is realized in order to choose the appropriate action.…”

Section: Related Workmentioning

confidence: 99%

Real-time obstacle avoidance for polygonal robots with a reduced dynamic window

Arras

Persson

Tomatis

et al.

Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292)

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IntroductionIn most mobile robot applications, unmodeled obstacles in the environment make it necessary to locally replan a path in order to attain a goal autonomously. Obstacle or collision avoidance is the motion generating component in a robot's architecture with this purpose. Although a considerable amount of work on obstacle avoidance for mobile robots exist, many approaches are still restricted to a certain robot setting. Common restrictions are a simplified robot shape (mainly circular), a high sensitivity to local minima or impractical computational requirements for real-time if the former two points shall be met. Related WorkEarly work in this topic includes the potential field approach where the robot complies to a superposed force field from obstacles and the goal [6]. It has been shown that this approach suffers from many shortcomings, for example the sensitivity to local minima [9]. Further developments improve the classical approach: In [8] the driving behavior of the vehicle is improved by a decomposition of the field into a rotation potential field and a task potential field . The problem of local minima is addressed in [4] using a harmonic potential field based on an analogy from fluid dynamics.In [12] the elastic band concept is proposed which is further extended in [7] to non-holonomic robots. A bubble is defined as the maximal collision-free space around the robot. They are then used to form a band of bubbles connecting the start with the goal point. Although it is a global path planning method, local obstacle avoidance is realized by adapting the bubble band to unmodeled objects during traversal.In [11] the concept of the nearness diagram is presented identifying five different navigation laws according to a robot security measure. In choosing different motion commands for each of the five cases, a simple reasoning is realized in order to choose the appropriate action.In contrast to this are approaches which deduce a motion command from the current sensor readings by applying a single rule. This rule then yields a steering angle [16] [16] has been ameliorated in [17] with a look-ahead functionality: An A*-algorithm searches for the proper action on a spatial tree spanned by a set of candidate directions. Looking ahead is based either on an a priori map or the current local map. In [15] the lane curvature approach overcomes problems in [14] which came from the assumption that the robot always moves on circular arcs.[3] presents a globalized version of the dynamic window approach. In combination with a NF1 path planner (see below) on a incrementally built open-loop map, a minima-free path planning is achieved provided that the map remains globally consistent. The dynamic window with a NF1 path planner is also used in [13] where a noncircular robot shape is assumed. Real-time capability is achieved by using a robot-specific look-up table.With the exception of [7] and [13] all propositions use a circular shaped robot. But in many scenarios for service and personal robots, it is the appl...

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“…Then, these methods are susceptible to failure when the vehicle dynamics take an important role: (1) Systems working at high speeds, or (2) systems with slow dynamics. Examples of these methods include: Potential Field methods [1], Vector Field Histogram [2], [3], Elastic Band [4], Elastic Strips [5], Nearness Diagram Navigation [6].…”

Section: Introductionmentioning

confidence: 99%

“…To demonstrate and validate the usefulness of this framework, we have extended and experimentally tested two reactive collision avoidance approaches that do not address the dynamic constraints into their formulation -the Potential Field method [1] and the Nearness Diagram Navigation [6].…”

Section: Introductionmentioning

confidence: 99%