Showing papers on "Motion planning published in 1992"

Exact robot navigation using artificial potential functions

Abstract: A methodology for exact robot motion planning and control that unifies the purely kinematic path planning problem with the lower level feedback controller design is presented. Complete information about a freespace and goal is encoded in the form of a special artificial potential function, called a navigation function, that connects the kinematic planning problem with the dynamic execution problem in a provably correct fashion. The navigation function automatically gives rise to a bounded-torque feedback controller for the robot's actuators that guarantees collision-free motion and convergence to the destination from almost all initial free configurations. A formula for navigation functions that guide a point-mass robot in a generalized sphere world is developed. The simplest member of this family is a space obtained by puncturing a disk by an arbitrary number of smaller disjoint disks representing obstacles. The other spaces are obtained from this model by a suitable coordinate transformation. Simulation results for planar scenarios are provided. >

Numerical potential field techniques for robot path planning

Abstract: An approach to robot path planning that consists of incrementally building a graph connecting the local minima of a potential field defined in the robot's configuration space and concurrently searching this graph until a goal configuration is attained is proposed. Unlike the so-called global path planning methods, this approach does not require an expensive computation step before the search for a path can actually start, and it searches a graph that is usually much smaller than the graph searched by the so-called local methods. A collection of effective techniques to implement this approach is described. They are based on the use of multiscale pyramids of bitmap arrays for representing both the robot's workspace and configuration space. This distributed representation makes it possible to construct potential fields numerically, rather than analytically. A path planner based on these techniques has been implemented. Experiments with this planner show that it is both very fast and capable of handling many degrees of freedom. >

Gross motion planning—a survey

Abstract: Motion planning is one of the most important areas of robotics research. The complexity of the motion-planning problem has hindered the development of practical algorithms. This paper surveys the work on gross-motion planning, including motion planners for point robots, rigid robots, and manipulators in stationary, time-varying, constrained, and movable-object environments. The general issues in motion planning are explained. Recent approaches and their performances are briefly described, and possible future research directions are discussed.

A potential field approach to path planning

Abstract: A path-planning algorithm for the classical mover's problem in three dimensions using a potential field representation of obstacles is presented. A potential function similar to the electrostatic potential is assigned to each obstacle, and the topological structure of the free space is derived in the form of minimum potential valleys. Path planning is done at two levels. First, a global planner selects a robot's path from the minimum potential valleys and its orientations along the path that minimize a heuristic estimate of the path length and the chance of collision. Then, a local planner modifies the path and orientations to derive the final collision-free path and orientations. If the local planner fails, a new path and orientations are selected by the global planner and subsequently examined by the local planner. This process is continued until a solution is found or there are no paths left to be examined. The algorithm solves a much wider class of problems than other heuristic algorithms and at the same time runs much faster than exact algorithms (typically 5 to 30 min on a Sun 3/260). >

Integration of representation into goal-driven behavior-based robots

Abstract: An architecture that integrates a map representation into a reactive, subsumption-based mobile robot is described. This fully integrated reactive system removes the distinction between the control program and the map. The method was implemented and tested on a mobile robot equipped with a ring of sonars and a compass, and programmed with a collection of simple, incrementally designed behaviors. The robot performs collision-free navigation, dynamic landmark detection, map construction and maintenance, and path planning. Given any known landmark as a goal, the robot plans and executes the shortest known path to it. If the goal is not reachable, the robot detects failure, updates the map, and finds an alternate route. The topological representation primitives are designed to suit the robot's sensors and its navigation behavior, thus minimizing the amount of stored information. Distributed over a collection of behaviors, the map itself performs constant-time localization and linear-time path planning. The approach is qualitative and robust. >

Nonholonomic Motion Planning

Abstract: Nonholonomic kinematics and the role of elliptic functions in constructive controllability, R.W. Brockett and L. Dai steering nonholonomic control systems using sinusoids, R.M. Murray and S. Shakar Sastry smooth time-periodic feedback solutions for nonholonomic motion planning, L. Gurvits and Zexiang Li lie bracket extensions and averaging - the single-bracket case, H.J. Sussmann and Wensheng Liu singularities and topological aspects in nonholonomic motion planning, J.-P. Laumond motion planning for nonholonomic dynamic systems, M. Reyhanoglu et al a differential geometric approach to motion planning, G. Lafferriere and H.J. Sussmann planning smooth paths for mobile robots, P. Jacobs and J. Canny nonholonomic control and gauge theory, R. Montgomery optimal nonholonomic motion planning for a falling cat, C. Fernandes et al nonholonomic behaviour in free-floating space manipulators and its utilization, E.G. Papadopoulos.

Coordinating locomotion and manipulation of a mobile manipulator

Abstract: A planning and control algorithm for coordinating the motion of a mobile manipulator is presented. The design criterion is to control the mobile platform so that the manipulator is maintained in a configuration which maximizes the manipulability measure. The effectiveness of the method was verified by simulations on two representative trajectories. The algorithm was implemented with an actual mobile manipulator and tested on one of the trajectories for comparison purposes. >

A mobile robot exploration algorithm

Abstract: An algorithm for path planning to a goal with a mobile robot in an unknown environment is presented. The robot maps the environment only to the extent necessary to achieve the goal. Mapping is achieved using tactile sensing while the robot is executing a path to the specified goal. Paths are generated by treating unknown regions in the environment as free space. As obstacles are encountered en route to a goal, the model of the environment is updated and a new path to the goal is planned and executed. Initially the paths to the goal generated by this algorithm will be negotiable paths. However, as the robot acquires more knowledge about the environment, the length of the planned paths will be optimized. The optimization criteria can be modified to favor or avoid unexplored regions in the environment. The algorithm makes use of the quadtree data structure to model the environment and uses the distance transform methodology to generate paths for the robot to execute. >

Fast Vision-guided Mobile Robot Navigation Using Model-based Reasoning And Prediction Of Uncertainties

Abstract: The model-based vision system described in this thesis allows a mobile robot to navigate indoors at an average speed of 8 meters/minute using ordinary laboratory computing hardware of approximately 16 MIPS power. The navigation capabilities of the robot are not impaired by the presence of the stationary or moving obstacles. The vision system maintains a model of uncertainty and keeps track of the growth of uncertainty as the robot travels towards the goal position. The estimates of uncertainty are then used to predict bounds on the locations and orientations of landmarks expected to be seen in a monocular image. This greatly reduces the search for establishing correspondence between the features visible in the image and the landmarks. Given a sequence of image features and a sequence of landmarks derived from a geometric model of the environment, a special aspect of our vision system is the sequential reduction in the uncertainty as each image feature is matched successfully with a landmark, allowing subsequent features to be matched more easily, this being a natural byproduct of the manner in which we use Kalman-filter based updating. Strategies for path planning, path replanning and perception planning are introduced for the robot to navigate in the presence of obstacles. Finally, experimental results are presented.

Path planning for a mobile robot

Abstract: Two problems for path planning of a mobile robot are considered. The first problem is to find a shortest-time, collision-free path for the robot in the presence of stationary obstacles in two dimensions. The second problem is to determine a collision-free path (greedy in time) for a mobile robot in an environment of moving obstacles. The environment is modeled in space-time and the collision-free path is found by a variation of the A* algorithm. >

AUV path planning: an A* approach to path planning with consideration of variable vehicle speeds and multiple, overlapping, time-dependent exclusion zones

Abstract: The authors describe an implementation of a path planner suitable for an autonomous underwater vehicle (AUV). The path planning unit is capable of maintaining a quadtree database of depth information, obstacles, and exclusion zones: verifying a previously planned path; generating a new path between successive goal points; and generating a path to the nearest point of a safe region. If a path does not exist within the given constraints, the path planner returns a reason for the failure. The path planner attempts to find a 3D corridor that does not intersect any nonentry zones. An A* algorithm is used to generate path corridors along great circle routes. The path planner's real-time performance in open, constricted, and real-world situations is discussed. Additional factors affecting performance such as the number of different vehicle speeds, the quadtree resolution, and the number of nonentry zones blocking the goal are considered. >

An introduction to motion planning under multirate digital control

Abstract: The authors propose digital control methods for steering real analytic controllable systems between arbitrary state configurations. The main idea is to achieve a multirate sampled procedure to perform motions in all the directions of controllability under piecewise constant controls. When it is applied to non-holonomic control systems without drift, the procedure simplifies. In particular, it results in exact steering on chained systems recently introduced in the motion planning literature. A classical example is reported. >

Landmark-based robot navigation

Abstract: To operate in the real world robots must deal with errors in control and sensing. Achieving goals despite these errors requires complex motion planning and plan monitoring. We present a reduced version of the general problem and a complete planner that solves it in polynomial time. The basic concept underlying this planner is that of a landmark. Within the field of influence of a landmark, robot control and sensing are perfect. Outside any such field control is imperfect and sensing is null. In order to make sure that the above assumptions hold, we may have to specifically engineer the robot workspace. Thus, for the first time, workspace engineering is seen as a means to make planning problems tractable. The planner was implemented and experimental results are presented. An interesting feature of the planner is that it always returns a universal plan in the form of a collection of reaction rules. This plan can be used even when the input problem has no guaranteed solution, or when unexpected events oceur during plan execution.

SANDROS: a motion planner with performance proportional to task difficulty

Abstract: To address the need of a practical motion planner for manipulators, the authors present an efficient and resolution-complete algorithm that has performance commensurate with task difficulty. The algorithm uses SANDROS, a search strategy that combines hierarchical, nonuniform multiresolution, and best-first search to find a near-optimal solution in the configuration space. This algorithm can be applied to any manipulator, and has been tested with five- and six-degree-of-freedom robots, with execution times ranging from 20 seconds to 10 minutes on a 16 MIPS workstation. >

Theory and Applications of Problem Solving

Abstract: Problem Representations. Problem Solving. World Representations at Different Granularities. The Relation Between Different Grain Size Worlds. Semi-Order Lattice. Attribute-Preserving. Selection and Adjustments of Grain-Sizes. Mergence. Decomposition. Conclusions. Hierarchy. The Model of Hierarchy. The Estimation of Computational Complexity. The Assumptions. The Estimation of The Complexity Under Deterministic Model. The Estimation of The Complexity Under Probabilistic Model. Successive Operation in Hierarchy. The Extraction of Information on High Abstraction Level. Examples. Constructing [f] Under Unstructured Domain. Constructing [f] Under Structured Domain. Conclusions. Fuzzy Equivalence Relation and Hierarchy. Fuzzy Quotient Structure. Cluster. Combination. Introduction. The Mathematical Model of Combination. The Combination of Domains. The Combination of Topologic Structure. The Combination of Semi-Order Structure. The Graphical Constructing Method of Quotient Semi-Order. The Combination of Semi-Order Structure. The Combination of Attribute Functions. The Combination Principle of Attribute Functions. Examples. Conclusions. Reasoning Model. Reasoning Models. Inference Network (I). Projection. Combination. Inference Network (II). Modeling. The Projection of AND/OR Relations. The Combination of AND/OR Relations. Operations and Quotient Structures. The Existence of Quotient Operation. Construction of Quotient Operations. The Approximation of Quotient Operation. Constraints and Quotient Constraints. Qualitative Reasoning. Qualitative Reasoning Model. Examples. The Procedure of Qualitative Reasoning. Planning. Automatic Generation of Assembly Sequences. Algorithms. Examples. Computational Complexity. Conclusions. Geometrical Methods of Motion Planning. Configuration Space Representation. Finding Collision-Free Paths. Topological Model of Motion Planning. Rotation Mapping Graph (RMG). The Topologic Model of Motion Planning. Homotopically Equivalent Classification. Dimension Reduction Method. Basic Principle. Characteristic Network. Applications. Collision-Free Paths Planning For A Planar Rod. Motion Planning For A Multi-Joint Arm. The Application of The Hierarchical Technique. The Hierarchical Motion Planning of Multi-Joint Arm. Estimation of The Computational Complexity. Statistical Heuristic Search. Statistical Inference Method in Heuristic Search. Heuristic Search. Statistical Inference. Statistical Heuristic Search. The Computational Complexity. The Model of Search Tree. SPA Search. SAA Search. Different Kinds of SA. The Extraction of Global Information. Hypothesis I. The Extraction of Global Statistic. Algorithm SA. The Comparison Between the Statistical Heuristic Search and A* . Comparison With A*. Comparison To Other Weighted Techniques. General Graph Search. Conclusions. References.

Using skeletons for nonholonomic path planning among obstacles

Abstract: The authors describe a practical path planner for nonholonomic robots in environments with obstacles. The planner is based on building a one-dimensional, maximal clearance skeleton through the configuration space of the robot. Rather than using the Euclidean metric to determine clearance, a special metric which captures information about the nonholonomy of the robot is used. The robot navigates from start to goal states by loosely following the skeleton. The resulting paths taken by the robot are of low complexity. Much of the computation can be done offline for a given robot, making for an efficient planner. The focus is on path planning for mobile robots, particularly the planar two-axle car, but the underlying ideas may be applied to planners for other nonholonomic robots. >

Theory and applications of hyper-redundant robotic manipulators

Abstract: The term "hyper-redundant" refers to robotic manipulators and mobile robots with a very large, possibly infinite, number of actuatable degrees of freedom. These robots are analogous in morphology and operation to snakes, worms, elephant trunks, and tentacles. This thesis presents a novel kinematic framework for hyper-redundant manipulator motion planning and task implementation. The basis of this formulation is the use of a "backbone reference set" which captures the essential macroscopic geometric features of hyper-redundant robots. In the analytical part of this work, the backbone representation is developed and used to solve problems in obstacle avoidance, locomotion, grasping, and "optimal" end effector placement. The latter part of this thesis deals with the design and implementation of a thirty-degree-of-freedom planar hyper-redundant manipulator which is used to demonstrate these novel kinematic and motion planning techniques. Design issues such as robustness with respect to mechanical failure, and design for easy assembly and repair are also addressed. The analytical and design concepts are combined to illustrate tasks for which hyper-redundant robotic mechanisms are well suited.

Exponential control law for a mobile robot: extension to path following

Abstract: The authors present an exponentially stable controller for a two-degree-of-freedom robot with nonholonomic constraints. Although this system is controllable, it has been shown to be nonstabilizable via smooth state feedback. A particular class of piecewise continuous controller which exponentially stabilizes the robot about the origin was previously proposed by the authors (1991). This approach is extended to stabilize about an arbitrary position and orientation, and to track a sequence of points. This feedback law is naturally combined with path planning when the desired path to be followed can be composed of a sequence of straight lines and circle segments, i.e. shortest paths of bounded curvature in the plane. >

Motion Planning of Multiple Mobile Robots

Abstract: As mobile robots expand their working area, motion planning of multiple mobile robots becomes more important than ever. In this paper, various researches are surveyed and categorized from the two viewpoints: c entralized / decentralized mechanism, and o n-1 i ne/o ff- line system. Since three kinds of combinations may be realizable, the three are discussed. The imotion planning of a group of mobile robots is also discussed. It is difficult to evaluate each research. We therefore proposed two standard problems. The first has 8 mobile robot!; who come easily to a deadlock. The second includes 2 groups of 4 robots respectively, which needs cooperative actions to each other.

HANDEY: A Robot Task Planner

Abstract: Part 1 Introduction: HANDEY robot programming why is robot programming difficult? what HANDEY is and is not. Part 2 Planning pick-and-place operations: examples of constraint interactions a brief overview of HANDEY the HANDEY planners combining the planners previous work. Part 3 Basics: polyhedral models robot models world models configuration space. Part 4 Gross motion planning: approximating the COs for revolute manipulators slice projections for polyhedral links efficiency considerations searching for paths a massively parallel algorithm. Part 5 Grasp planning: basic assumptions grasp planner overview using depth data in grasp planning the potential-field planner. Part 6 Regrasp planning: grasps placements on a table constructing the legal grasp/placement pairs solving the regrasp problem in handey an example computing the constraints regrasping using two parallel-jaw grippers. Part 7 Co-ordinating multiple robots: co-ordination and parallelism robot co-ordination as a scheduling problem the task completion diagram generating the TC diagram more on schedules other issues. Part 8 Conclusion: evolution path planning experimentation what we learned. (Part contents)

Deadlock-free motion planning using the Laplace potential field

Abstract: In this paper we introduce a motion planning method which uses an artificial potential field obtained by solving Laplace's differential equation. A potential field based on Laplace's equation has no minimal point; therefore, path planning is performed without falling into local minima. Furthermore, we propose an application of the motion planning method for recursive motion planning in an uncertain environment. We illustrate the robot motion generated by the proposed method with simulation examples.

Trajectory filtering and prediction for automated tracking and grasping of a moving object

Abstract: The authors explore the requirements for grasping a moving object. This task requires proper coordination between at least three separate subsystems: real-time vision sensing, trajectory-planning/arm-control, and grasp planning. As with humans, the system first visually tracks the object's 3D position. Because the object is in motion, this must be done in real-time to coordinate the motion of the robotic arm as it tracks the object. The vision system is used to feed an arm control algorithm that plans a trajectory. The arm control algorithm is implemented into two steps: filtering and prediction and kinematic transformation computation. Once the trajectory of the object is tracked, the hand must intercept the object to actually grasp it. Experimental results are presented in which which a moving model train was tracked, stably grasped, and picked up by the system. >

Experiments in dual-arm manipulation planning

Abstract: The problem of dual-arm manipulation planning is to plan the path of two cooperating robot arms to carry a moveable object from a given initial configuration to a given goal configuration amidst obstacles. The authors survey previous work in manipulation planning and relate it to this analysis. A formal configuration space presentation of the problem is given. Three implemented planners are described. These three planners operated in a two-dimensional workspace and addressed increasingly difficult versions of the dual-arm manipulation problem. They were implemented in the C language. Execution times given were obtained by running them on a DEC 5000 workstation. >

Averaging approach to nonholonomic motion planning

Abstract: The author considers the problem of motion planning for a nonholonomic system with drift. Open-loop and feedback solutions for nonholonomic motion planning (NMP) are constructed by using the averaging technique that is well known in applied mathematics. An algorithm for open-loop and feedback solutions of NMP is introduced. The main step in the algorithm is the case of first order Lie brackets. This case, as is shown, is equivalent to NMP for Brockett's system considered over functional commutative algebra. Feedback solutions are constructed in the same manner. From a robotics point of view, it is shown that NMP can be reduced to the holonomic problem. As linear algebra plays a crucial role in linear control theory, polylinear algebra is crucial for NMP. The rolling disk example is used to illustrate the feedback algorithm. >

Path Planning For Space Manipulators Exhibiting Nonholonomic Behavior

Abstract: Nonholonomic behavior is observed in free-floating manipulator systems, and is due to the nonintegrability of the angular momentum. Free-floating manipulators exhibit dynamic singularities which cannot be predicted by the kinematic properties of the system and whose location in the workspace is path dependent. Trouble-free Path Independent Workspaces are defined. A joint space planning technique used to control the orientation of the spacecraft by using joint manipulator motions is reviewed, and its limitations are discussed. Finally, a Cartesian space planning method that permits the effective use of a system’s reachable workspace by planning paths that avoid dynamically singular configurations is proposed and demonstrated by an example.

Backward assembly planning with assembly cost analysis

Abstract: The author considers automatic assembly planning by developing a backward assembly planner which handles the case where an assembly sequence is not the same as the reverse of a disassembly sequence; improving planning efficiency with the reduction of search space by merging and grouping parts based on interconnection feasibility and special process precedence constraints; establishing assembly process planning by incorporating such special processes as testing, cleaning, etc., in assembly planning; and providing subassembly evaluation criteria with a direct connection to assembly cost. A method for the stability and directionality of an assembly is presented through which the required number of holding devices and reorientations during assembly are identified. >

Minimum-time collision-free trajectory planning for dual-robot systems

Abstract: Collision-free multirobot motion planning can be achieved in two steps: path planning and trajectory planning. Path planning finds for the robots geometric paths to avoid collision with static obstacles and trajectory planning determines how fast each robot must move along its geometric path to avoid collision with other moving robots. For a dual-robot system, a simple trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position to avoid collision with the other robot. A sufficient condition under which this simple (thus easy to implement) strategy for dual-robot systems can achieve time optimality as well as collision avoidance, i.e., the two robots reach their final positions without colliding with each other in the minimum amount of time, is derived. A demonstrative example is presented, showing how this strategy can be used for loading and unloading applications. >