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Showing papers on "Motion planning published in 2000"


Proceedings ArticleDOI
24 Apr 2000
TL;DR: A simple and efficient randomized algorithm is presented for solving single-query path planning problems in high-dimensional configuration spaces by incrementally building two rapidly-exploring random trees rooted at the start and the goal configurations.
Abstract: A simple and efficient randomized algorithm is presented for solving single-query path planning problems in high-dimensional configuration spaces. The method works by incrementally building two rapidly-exploring random trees (RRTs) rooted at the start and the goal configurations. The trees each explore space around them and also advance towards each other through, the use of a simple greedy heuristic. Although originally designed to plan motions for a human arm (modeled as a 7-DOF kinematic chain) for the automatic graphic animation of collision-free grasping and manipulation tasks, the algorithm has been successfully applied to a variety of path planning problems. Computed examples include generating collision-free motions for rigid objects in 2D and 3D, and collision-free manipulation motions for a 6-DOF PUMA arm in a 3D workspace. Some basic theoretical analysis is also presented.

3,102 citations


Proceedings ArticleDOI
24 Apr 2000
TL;DR: The overall theme of the algorithm, called Lazy PRM, is to minimize the number of collision checks performed during planning and hence minimize the running time of the planner.
Abstract: Describes an approach to probabilistic roadmap planners (PRMs). The overall theme of the algorithm, called Lazy PRM, is to minimize the number of collision checks performed during planning and hence minimize the running time of the planner. Our algorithm builds a roadmap in the configuration space, whose nodes are the user-defined initial and goal configurations and a number of randomly generated nodes. Neighboring nodes are connected by edges representing paths between the nodes. In contrast with PRMs, our planner initially assumes that all nodes and edges in the roadmap are collision-free, and searches the roadmap at hand for a shortest path between the initial and the goal node. The nodes and edges along the path are then checked for collision. If a collision with the obstacles occurs, the corresponding nodes and edges are removed from the roadmap. Our planner either finds a new shortest path, or first updates the roadmap with new nodes and edges, and then searches for a shortest path. The above process is repeated until a collision-free path is returned. Lazy PRM is tailored to efficiently answer single planning queries, but can also be used for multiple queries. Experimental results presented in the paper show that our lazy method is very efficient in practice.

874 citations


Journal ArticleDOI
01 Oct 2000
TL;DR: New repulsive potential functions are presented by taking the relative distance between the robot and the goal into consideration, which ensures that the goal position is the global minimum of the total potential.
Abstract: The paper first describes the problem of goals unreachable with obstacles nearby when using potential field methods for mobile robot path planning. Then, new repulsive potential functions are presented by taking the relative distance between the robot and the goal into consideration, which ensures that the goal position is the global minimum of the total potential.

773 citations


Proceedings ArticleDOI
28 Jun 2000
TL;DR: A two step path-planning algorithm for UAVs that generates a stealthy path through a set of enemy radar sites of known location, and provides an intuitive way to trade-off stealth versus path length is proposed.
Abstract: In this paper, a two step path-planning algorithm for UAVs is proposed. The algorithm generates a stealthy path through a set of enemy radar sites of known location, and provides an intuitive way to trade-off stealth versus path length. In the first step, a suboptimal rough-cut path is generated through the radar sites by constructing and searching a graph based on Voronoi polygons. In the second step, a set of nonlinear ordinary differential equations are simulated, using the graph solution as an initial condition. The ODEs describe the dynamics of a set of virtual masses located in a virtual force field. The virtual forces push the masses away from the radar and toward one another. The ODEs are simulated to find a locally, exponentially stable equilibrium solution, which is interpreted as the optimal path. A simulation is provided to illustrate the idea.

363 citations


Proceedings ArticleDOI
01 Dec 2000
TL;DR: In this paper, the authors propose a control architecture based on a hybrid automaton, the states of which represent feasible trajectory primitives for the vehicle, in the presence of disturbances and uncertainties in the plant and/or in the environment.
Abstract: The operation of an autonomous vehicle in an unknown, dynamic environment is a very complex problem, especially when the vehicle is required to use its full maneuvering capabilities, and to react in real time to changes in the operational environment. A possible approach to reduce the computational complexity of the motion planning problem for a nonlinear, high dimensional system, is based on a quantization of the system dynamics, leading to a control architecture based on a hybrid automaton, the states of which represent feasible trajectory primitives for the vehicle. The paper focuses on the feasibility of this approach, in the presence of disturbances and uncertainties in the plant and/or in the environment: the structure of a robust hybrid automaton is defined and its properties are analyzed. In particular, we address the issues of well-posedness, consistency and reachability. For the case of autonomous vehicles, we provide sufficient conditions to guarantee reachability of the automaton.

360 citations


Journal ArticleDOI
TL;DR: A variant of probabilistic roadmap methods (PRM) that recently appeared as a promising approach to motion planning is presented, exploiting a free-space structuring of the configuration space into visibility domains in order to produce small roadmaps, called visibility roadmaps.
Abstract: This paper presents a variant of probabilistic roadmap methods (PRM) that recently appeared as a promising approach to motion planning. We exploit a free-space structuring of the configuration space into visibility domains in order to produce small roadmaps, called visibility roadmaps. Our algorithm integrates an original termination condition related to the volume of the free space covered by the roadmap. The planner has been implemented within a software platform allowing us to address a large class of mechanical systems. Experiments show the efficiency of the approach, in particular for capturing narrow passages of collision-free configuration spaces.

353 citations


Journal ArticleDOI
TL;DR: A new approach based on interval analysis is developed to find the global minimum-jerk trajectory of a robot manipulator within a joint space scheme using cubic splines, and the resulting MJ trajectory planning is shown to be a global constrained minimax optimization problem.
Abstract: A new approach based on interval analysis is developed to find the global minimum-jerk (MJ) trajectory of a robot manipulator within a joint space scheme using cubic splines. MJ trajectories are desirable for their similarity to human joint movements and for their amenability to path tracking and to limit robot vibrations. This makes them attractive choices for robotic applications, in spite of the fact that the manipulator dynamics are not taken into account. Cubic splines are used in a framework that assures overall continuity of velocities and accelerations in the robot movement. The resulting MJ trajectory planning is shown to be a global constrained minimax optimization problem. This is solved by a newly devised algorithm based on interval analysis and proof of convergence with certainty to an arbitrarily good global solution is provided. The proposed planning method is applied to an example regarding a six-joint manipulator and comparisons with an alternative MJ planner are exposed.

343 citations


Journal ArticleDOI
24 Apr 2000
TL;DR: The concept of "dynamics filter" is proposed which transforms a physically inconsistent motion into a consistent one, and an example of its implementation using feedback control and local optimization is provided.
Abstract: Humanoid robots are required to make a variety of dynamics and even expressive motions in changing environments. However, the conventional methods for generating humanoid motions fail do achieve this requirement since they can only generate quite artificial and predefined motions through rather complicated optimization processes. In this paper, we propose the concept of "dynamics filter" which transforms a physically inconsistent motion into a consistent one, and provide an example of its implementation using feedback control and local optimization. The optimization is based on the equation of motion of constrained kinematic chains, which is derived from our previously proposed method for computing the dynamics of structure-varying kinematic chains. The proposed method can be applied to online motion generator of humanoid robots.

325 citations


Proceedings ArticleDOI
16 Jul 2000
TL;DR: Simulation results show that the proposed EAPF methodology is efficient and robust for robot path planning with non-stationary goals and obstacles.
Abstract: A new methodology named Evolutionary Artificial Potential Field (EAPF) is proposed for real-time robot path planning. The artificial potential field method is combined with genetic algorithms, to derive optimal potential field functions. The proposed EAPF approach is capable of navigating robot(s) situated among moving obstacles. Potential field functions for obstacles and goal points are also defined. The potential field functions for obstacles contain tunable parameters. The multi-objective evolutionary algorithm (MOEA) is utilized to identify the optimal potential field functions. Fitness functions such as goal-factor, obstacle-factor, smoothness-factor and minimum-pathlength-factor are developed for the MOEA selection criteria. An algorithm named escape-force is introduced to avoid the local minima associated with EAPF. Moving obstacles and moving goal positions were considered to test the robust performance of the proposed methodology. Simulation results show that the proposed methodology is efficient and robust for robot path planning with non-stationary goals and obstacles.

311 citations


Journal ArticleDOI
TL;DR: This paper defines the HGVG structure: a robot can plan a path between two locations in its work space or configuration space by simply planning a path onto the HNVG, then along the HCVG, and finally from theHGVG to the goal.
Abstract: The hierarchical generalized Voronoi graph (HGVG) is a new roadmap developed for sensor-based exploration in unknown environments. This paper defines the HGVG structure: a robot can plan a path between two locations in its work space or configuration space by simply planning a path onto the HGVG, then along the HGVG, and finally from the HGVG to the goal. Since the bulk of the path planning occurs on the one-dimensional HGVG, motion planning in arbitrary dimensioned spaces is virtually reduced to a one-dimensional search problem. A bulk of this paper is dedicated to ensuring the HGVG is sufficient for motion planning by demonstrating the HGVG (with its links) is an arc-wise connected structure. All of the proofs in this paper that lead toward the connectivity result focus on a large subset of spaces in R3, but wherever possible, results are derived in Rm. In fact, under a strict set of conditions, the HGVG (the GVG by itself) is indeed connected, and hence sufficient for motion planning. The chief advanta...

288 citations


Journal ArticleDOI
TL;DR: This work presents a novel route planning approach to generate mission-adaptable routes in an accurate and efficient manner that is able to take into account various mission constraints including: minimum route leg length, maximum turning angle, route distance constraint, and fixed approach vector to goal position.
Abstract: Route planning for intelligent guidance and navigation systems is an extremely complex problem with both military and commercial applications. Standard route planning algorithms usually generate a minimum cost route based on a predetermined cost function. Unfortunately, such a solution may not represent a desirable route for various mission scenarios. We present a novel route planning approach to generate mission-adaptable routes in an accurate and efficient manner. The routes are computed in real-time and are able to take into account various mission constraints including: minimum route leg length, maximum turning angle, route distance constraint, and fixed approach vector to goal position.

Proceedings ArticleDOI
14 Aug 2000
TL;DR: In this paper, a hierarchical decomposition approach is pursued for path planning of multiple UAVs, so as to jointly reach a target area while minimizing the flight's exposure to radar, and the coordination of the UAV's arrival at the target area is performed by the higher level coordination agent.
Abstract: Path planning arid coordination of multiple unmanned air vehicles, so as to jointly reach a target area while minimizing the flight's exposure to radar is addressed. A hierarchical decomposition approach is pursued. The optimal path planning for a single vehicle is performed to minimize exposure while a timing constraint is imposed. Each vehicle plans it's own path. The path planning consists of a two step procedure. First, a polygonal path to the optimal path is obtained. Second, the initial path is refined to a flyable path by acknowledging maneuverability constraints. The coordination of the timing of the vehicles' arrival at the target area is performed by the higher level coordination agent. The coordination agent calculates a team estimated time of arrival from a sensitivity function that is calculated and communicated by each of the UAVs. This approach is illustrated in a simulation of a simplified scenario where three UAVs are coordinated to arrive at the target area simultaneously. Popup threats are introduced that result in dynamic inflight replanning. Simulation results show that coarse grid planning and decentralized coordinated control can rapidly respond to new threats while satisfying rigid rendezvous timing constaints.

Journal ArticleDOI
TL;DR: A biologically inspired neural network approach to real-time collision-free motion planning of mobile robots or robot manipulators in a nonstationary environment is proposed and is guaranteed by qualitative analysis and the Lyapunov stability theory.

Journal ArticleDOI
01 Dec 2000
TL;DR: A mathematical model of the robot's motion was developed using the nonholonomic constraints on its motion, and it is shown experimentally that the model agrees well with the results.
Abstract: Describes a prototype and analytical studies of a spherical rolling robot, a new design of a nonholonomic robot system. The spherical robot is driven by two remotely controlled, internally mounted rotors that induce the ball to roll and spin on a flat surface. It is tracked on the plane by an overhead camera. A mathematical model of the robot's motion was developed using the nonholonomic constraints on its motion. For a number of simple motions, it is shown experimentally that the model agrees well with the results. Methods were developed for planning feasible, minimum time and minimum energy trajectories for the robot. These methods are illustrated both by mathematical simulation and hardware experiments.

Journal ArticleDOI
01 Feb 2000
TL;DR: Probabilistic self-localization techniques for mobile robots that are based on the principle of maximum-likelihood estimation are described, which performs an efficient global search of the pose space that guarantees that the best position is found according to the probabilistic map agreement measure in a discretized pose space.
Abstract: We describe probabilistic self-localization techniques for mobile robots that are based on the principle of maximum-likelihood estimation. The basic method is to compare a map generated at the current robot position with a previously generated map of the environment in order to probabilistically maximize the agreement between the maps. This method is able to operate in both indoor and outdoor environments using either discrete features or an occupancy grid to represent the world map. The map may be generated using any method to detect features in the robot's surroundings, including vision, sonar, and laser range-finder. We perform an efficient global search of the pose space that guarantees that the best position is found according to the probabilistic map agreement measure in a discretized pose space. In addition, subpixel localization and uncertainty estimation are performed by fitting the likelihood function with a parameterized surface. We describe the application of these techniques in several experiments.

Journal ArticleDOI
TL;DR: A new extension of EP/N computes a safe-optimum path of a ship in given static and dynamic environments, and a safe trajectory of the ship in a collision situation is determined on the basis of this algorithm.
Abstract: For a given circumstance (i.e., a collision situation at sea), a decision support system for navigation should help the operator to choose a proper manoeuvre, teach him good habits, and enhance his general intuition on how to behave in similar situations in the future. By taking into account certain boundaries of the maneuvering region along with information on navigation obstacles and other moving ships, the problem of avoiding collisions is reduced to a dynamic optimization task with static and dynamic constraints. This paper presents experiments with a modified version of the Evolutionary Planner/Navigator (EP/N). Its new version, /spl thetav/EP/N++, is a major component of a such decision support system. This new extension of EP/N computes a safe-optimum path of a ship in given static and dynamic environments. A safe trajectory of the ship in a collision situation is determined on the basis of this algorithm. The introduction of a time parameter, the variable speed of the ship, and time-varying constraints representing movable ships are the main features of the new system. Sample results of ship trajectories obtained for typical navigation situations are presented.

Proceedings ArticleDOI
31 Oct 2000
TL;DR: A solution to realtime motion control that can competently maneuver a robot at optimal speed even as it explores a new region or encounters new obstacles is presented.
Abstract: Despite many decades of research into mobile robot control, reliable, high-speed motion in complicated, uncertain environments remains an unachieved goal. In this paper we present a solution to realtime motion control that can competently maneuver a robot at optimal speed even as it explores a new region or encounters new obstacles. The method uses a navigation function to generate a gradient field that represents the optimal (lowest-cost) path to the goal at every point in the workspace. Additionally, we present an integrated sensor fusion system that allows incremental construction of an unknown or uncertain environment. Under modest assumptions, the robot is guaranteed to get to the goal in an arbitrary static unexplored environment, as long as such a path exists. We present preliminary experiments to show that the gradient method is better than expert human controllers in both known and unknown environments.

Journal ArticleDOI
TL;DR: It is shown that the feature concept is also useful in assembly modeling and planning, and an integrated object-oriented product model is introduced that can considerably help in both assembly modeled and planning.
Abstract: In recent years, features have been introduced in modeling and planning for manufacturing of parts. Such features combine geometric and functional information. Here it is shown that the feature concept is also useful in assembly modeling and planning. For modeling and planning of both single parts and assemblies, an integrated object-oriented product model is introduced. For specific assembly-related information, assembly features are used. Handling features contain information for handling components, connection features information on connections between components. A prototype modeling environment has been developed. The product model has been successfully verified within several analyses and planning modules, in particular stability analyses, grip planning, motion planning and assembly sequence planning. Altogether, feature-based product models for assembly can considerably help in both assembly modeling and planning, on the one hand by integrating single-part and assembly modeling, and on the other hand by integrating modeling and planning.

Proceedings ArticleDOI
Ileana Streinu1
12 Nov 2000
TL;DR: A combinatorial approach to plan noncolliding motions for a polygonal bar-and-joint framework based on a novel class of one-degree-of-freedom mechanisms induced by pseudo triangulations of planar point sets that yields very efficient deterministic algorithms for a category of robot arm motion planning problems with many degrees of freedom.
Abstract: We propose a combinatorial approach to plan noncolliding motions for a polygonal bar-and-joint framework. Our approach yields very efficient deterministic algorithms for a category of robot arm motion planning problems with many degrees of freedom, where the known general roadmap techniques would give exponential complexity. It is based on a novel class of one-degree-of-freedom mechanisms induced by pseudo triangulations of planar point sets, for which we provide several equivalent characterization and exhibit rich combinatorial and rigidity theoretic properties. The main application is an efficient algorithm for the Carpenter's rule problem: convexify a simple bar-and-joint planar polygonal linkage using only non self-intersecting planar motions. A step in the convexification motion consists in moving a pseudo-triangulation-based mechanism along its unique trajectory in configuration space until two adjacent edges align. At that point, a local alteration restores the pseudo triangulation. The motion continues for O(n/sup 2/) steps until all the points are in convex position.

Proceedings ArticleDOI
01 Jan 2000
TL;DR: An algorithm which extends the probabilistic roadmap (PRM) framework to handle manipulation planning by using a two level approach, a PRM of PRMs, made possible by the introduction of a new kind of roadmap, called the fuzzy roadmap.
Abstract: This paper presents an algorithm which extends the probabilistic roadmap (PRM) framework to handle manipulation planning. This is done by using a two level approach, a PRM of PRMs. The first level builds a manipulation graph, whose nodes represent stable placements of the manipulated objects while the edges represent transfer and transit actions. The actual motion planning for the transfer and transit paths is done by PRM planners at the second level. The approach is made possible by the introduction of a new kind of roadmap, called the fuzzy roadmap. The fuzzy roadmap contains edges which are not verified by a local planner during construction. Instead, each edge is assigned a number which represents the probability that it is feasible. Later, if the edge is part of a solution path, the edge is checked for collisions. The overall effect is that our roadmaps evolve iteratively until they contain a solution. The use of fuzzy roadmaps in both levels of our manipulation planner offers many advantages. At the first level, a fuzzy roadmap represents the manipulation graph and addresses the problem of having probabilistically complete planners at the second level. At the second level, fuzzy roadmaps drastically reduce the number of collision checks. The paper contains experimental results demonstrating the feasibility and efficiency of our scheme.

Journal ArticleDOI
TL;DR: The behavior-programming control concept is suggested for networked mobile robot systems to avoid disturbances of the Internet latency and the event-driven concept is applied on the robot to switch the behaviors to accommodate the unpredicted mission autonomously.
Abstract: We review the networked mobile robot systems and suggest taxonomy based on the three levels of control commands. The performance analysis result shows that direct control has potential difficulty for implementation due to the unpredicted transmission delay of the network. To tackle this problem, we have suggested the behavior-programming control concept to avoid disturbances of the Internet latency. For this purpose, primitive local intelligence of the mobile robot is grouped into motion planner, motion executor, and motion assistant, where each of a group is treated as an agent. They are integrated by centralized control architecture based on multi-agent concept, communicated through a center information memory. The event-driven concept is applied on the robot to switch the behaviors to accommodate the unpredicted mission autonomously. We have successfully demonstrated experimentally the feasibility and reliability for system through a performance comparison with direct remote control.

Proceedings ArticleDOI
24 Apr 2000
TL;DR: The novelty of this technique is that the thermal resistance in the configuration space for all different orientations of the robot can be superimposed, which reduces a search on R/sup n//spl times/SO(n) to one on R-sup n/ followed by asearch on SO(n).
Abstract: Presents an artificial potential field method for path planning of non-spherical single-body robots. The model simulates steady-state heat transfer with variable thermal conductivity. The optimal path problem is then the same as a heat flow with minimal thermal resistance. The novelty of this technique is that the thermal resistance in the configuration space for all different orientations of the robot can be superimposed. This reduces a search on R/sup n//spl times/SO(n) to one on R/sup n/ followed by a search on SO(n). Examples are presented to demonstrate the approach.

Proceedings ArticleDOI
31 Oct 2000
TL;DR: This paper presents a new real-time collision avoidance approach for mobile robots that performs a high level information extraction and interpretation of the environment and uses this information to generate the motion commands.
Abstract: This paper presents a new real-time collision avoidance approach for mobile robots. The nearness diagram method (ND) performs a high level information extraction and interpretation of the environment. Subsequently, this information is used to generate the motion commands. The proposed approach is well-suited to deal with unknown, unstructured and dynamic environments, where problems of other approaches are avoided. Some experimental results are shown using an holonomic mobile base to demonstrate the usefulness of the method.

Journal ArticleDOI
TL;DR: This paper gives a complete description of the reachable manifold for general pairs of bodies, and a constructive controllability algorithm for planning rolling motions for dexterous robot hands.
Abstract: Pairs of bodies with regular rigid surfaces rolling onto each other in space form a nonholonomic system of a rather general type, posing several interesting control problems of which not much is known. The nonholonomy of such systems can be exploited in practical devices, which is very useful in robotic applications. In order to achieve all potential benefits, a deeper understanding of these types of systems and more practical algorithms for planning and controlling their motions are necessary. In this paper, we study the controllability aspect of this problem, giving a complete description of the reachable manifold for general pairs of bodies, and a constructive controllability algorithm for planning rolling motions for dexterous robot hands.

Proceedings ArticleDOI
24 Apr 2000
TL;DR: A randomized motion planner for kinodynamic asteroid avoidance problems, in which a robot must avoid collision with moving obstacles under kinematic, dynamic constraints and reach a specified goal state, inspired by probabilistic-roadmap techniques.
Abstract: This paper presents a randomized motion planner for kinodynamic asteroid avoidance problems, in which a robot must avoid collision with moving obstacles under kinematic, dynamic constraints and reach a specified goal state. Inspired by probabilistic-roadmap (PRM) techniques, the planner samples the state x time space of a robot by picking control inputs at random in order to compute a roadmap that captures the connectivity of the space. However, the planner does not precompute a roadmap as most PRM planners do. Instead, for each planning query, it generates, on the fly, a small roadmap that connects the given initial and goal state. In contrast to PRM planners, the roadmap computed by our algorithm is a directed graph oriented along the time axis of the space. To verify the planner's effectiveness in practice, we tested it both in simulated environments containing many moving obstacles and on a real robot under strict dynamic constraints. The efficiency of the planner makes it possible for a robot to respond to a changing environment without knowing the motion of moving obstacles well in advance.

Proceedings ArticleDOI
24 Apr 2000
TL;DR: This paper presents a framework that allows real-time replanning in high-dimensional configuration spaces, using proximity to the environment as a simple and effective heuristic and thereby significantly pruning the search in the configuration space.
Abstract: Real-time replanning is a prerequisite for motion execution in unpredictably changing environments. This paper presents a framework that allows real-time replanning in high-dimensional configuration spaces. Initially, a planning operation generates a path. The path is augmented by a set of paths homotopic to it. This set is represented implicitly by a volume of free space in the work space. Effectively, this corresponds to delaying part of the planning operation for the homotopic paths until motion execution. During execution reactive control algorithms are used to select a valid path from the set of homotopic paths, using proximity to the environment as a simple and effective heuristic and thereby significantly pruning the search in the configuration space. Experimental results are presented to validate the real-time performance of this framework in high-dimensional configuration spaces.

Proceedings ArticleDOI
24 Apr 2000
TL;DR: A decentralized formation control for executing elementary formation manoeuvres (EFM) for Hilare-type mobile robots with reduced communication among robots and the formation obtains certain robustness properties not available to other formation controls.
Abstract: This paper presents a decentralized formation control (the coupled dynamics approach) for executing elementary formation manoeuvres (EFM) for Hilare-type mobile robots. The concept of an EFM is presented. It is then shown that each of these EFMs possesses a common mathematical structure and thus may be executed by the same type of robot control. We present two EFM controls: the first control puts feedback on the relative motion and the global motion of each robot; and the second one adds inter-robot damping. The key advantage of our approach is the reduced communication among robots and the formation obtains certain robustness properties not available to other formation controls. We present the simulation and hardware results for each of these controls.

Journal ArticleDOI
01 Dec 2000
TL;DR: Intelligent sensing, planning, and control of a prototype robotic melon harvester that was tested in the field on two different melon cultivars during two different seasons and over 85% of the fruit were successfully detected and picked.
Abstract: Intelligent sensing, planning, and control of a prototype robotic melon harvester is described. The robot consists of a Cartesian manipulator mounted on a mobile platform pulled by a tractor. Black and white image processing is used to detect and locate the melons. Incorporation of knowledge-based rules adapted to the specific melon variety reduces false detections. Task, motion and trajectory planning algorithms and their integration are described. The intelligent control system consists of a distributed blackboard system with autonomous modules for sensing, planning and control. Procedures for evaluating performance of the robot performing in an unstructured and changing environment are described. The robot was tested in the field on two different melon cultivars during two different seasons. Over 85% of the fruit were successfully detected and picked.

Proceedings ArticleDOI
24 Apr 2000
TL;DR: An algorithm is presented for planar workspaces which operates in two steps: selecting art gallery-style guards and connecting them to form an inspection path which is extended to three dimensions and inspection paths are shown.
Abstract: Addresses the following inspection problem: given a known workspace and a robot with vision capabilities compute a short path path for the robot such that each point on boundary of the workspace is visible from some point on the path. Autonomous inspection, such as by a flying camera, or a virtual reality architectural walkthrough, could be guided by a solution to the above inspection problem. Visibility constraints on both maximum viewing distance and maximum angle of incidence are considered to better model real sensors. An algorithm is presented for planar workspaces which operates in two steps: selecting art gallery-style guards and connecting them to form an inspection path. Experimental results for this algorithm are discussed. Next, the algorithm is extended to three dimensions and inspection paths are shown.

Journal ArticleDOI
01 Mar 2000
TL;DR: The well-formulated and well-known laws of electrostatic fields are used to prove that the proposed approach generates an approximately optimal path (based on cell resolution) in a real-time frame.
Abstract: Proposes a solution to the two-dimensional (2-D) collision fee path planning problem for an autonomous mobile robot utilizing an electrostatic potential field (EPF) developed through a resistor network, derived to represent the environment. No assumptions are made about the amount of information contained in the a priori environment map (it may be completely empty) or the shape of the obstacles. The well-formulated and well-known laws of electrostatic fields are used to prove that the proposed approach generates an approximately optimal path (based on cell resolution) in a real-time frame. It is also proven through the classical laws of electrostatics that the derived potential function is a global navigation function (as defined by Rimon and Koditschek, 1992), that the field is free of all local minima and that all paths necessarily lead to the goal position. The complexity of the EPF generated path is shown to be O(mn/sub M/), where m is the total number of polygons in the environment and n/sub M/ is the maximum number of sides of a polygonal object. The method is tested both by simulation and experimentally on a Nomad200 mobile robot platform equipped with a ring of sixteen sonar sensors.