Showing papers in "IEEE Transactions on Robotics in 2005"

Coordinated multi-robot exploration

Abstract: In this paper, we consider the problem of exploring an unknown environment with a team of robots. As in single-robot exploration the goal is to minimize the overall exploration time. The key problem to be solved in the context of multiple robots is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of the environment. We present an approach for the coordination of multiple robots, which simultaneously takes into account the cost of reaching a target point and its utility. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced. In this way, different target locations are assigned to the individual robots. We furthermore describe how our algorithm can be extended to situations in which the communication range of the robots is limited. Our technique has been implemented and tested extensively in real-world experiments and simulation runs. The results demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission.

Fast replanning for navigation in unknown terrain

Abstract: Mobile robots often operate in domains that are only incompletely known, for example, when they have to move from given start coordinates to given goal coordinates in unknown terrain. In this case, they need to be able to replan quickly as their knowledge of the terrain changes. Stentz' Focussed Dynamic A/sup */ (D/sup */) is a heuristic search method that repeatedly determines a shortest path from the current robot coordinates to the goal coordinates while the robot moves along the path. It is able to replan faster than planning from scratch since it modifies its previous search results locally. Consequently, it has been extensively used in mobile robotics. In this article, we introduce an alternative to D/sup */ that determines the same paths and thus moves the robot in the same way but is algorithmically different. D/sup */ Lite is simple, can be rigorously analyzed, extendible in multiple ways, and is at least as efficient as D/sup */. We believe that our results will make D/sup */-like replanning methods even more popular and enable robotics researchers to adapt them to additional applications.

Vision-based global localization and mapping for mobile robots

Abstract: We have previously developed a mobile robot system which uses scale-invariant visual landmarks to localize and simultaneously build three-dimensional (3-D) maps of unmodified environments. In this paper, we examine global localization, where the robot localizes itself globally, without any prior location estimate. This is achieved by matching distinctive visual landmarks in the current frame to a database map. A Hough transform approach and a RANSAC approach for global localization are compared, showing that RANSAC is much more efficient for matching specific features, but much worse for matching nonspecific features. Moreover, robust global localization can be achieved by matching a small submap of the local region built from multiple frames. This submap alignment algorithm for global localization can be applied to map building, which can be regarded as alignment of multiple 3-D submaps. A global minimization procedure is carried out using the loop closure constraint to avoid the effects of slippage and drift accumulation. Landmark uncertainty is taken into account in the submap alignment and the global minimization process. Experiments show that global localization can be achieved accurately using the scale-invariant landmarks. Our approach of pairwise submap alignment with backward correction in a consistent manner produces a better global 3-D map.

Velocity and position control of a wheeled inverted pendulum by partial feedback linearization

Abstract: In this paper, the dynamic model of a wheeled inverted pendulum (eg, Segway, Quasimoro, and Joe) is analyzed from a controllability and feedback linearizability point of view First, a dynamic model of this underactuated system is derived with respect to the wheel motor torques as inputs while taking the nonholonomic no-slip constraints into considerations This model is compared with the previous models derived for similar systems The strong accessibility condition is checked and the maximum relative degree of the system is found Based on this result, a partial feedback linearization of the system is obtained and the internal dynamics equations are isolated The resulting equations are then used to design two novel controllers The first one is a two-level velocity controller for tracking vehicle orientation and heading speed set-points, while controlling the vehicle pitch (pendulum angle from the vertical) within a specified range The second controller is also a two-level controller which stabilizes the vehicle's position to the desired point, while again keeping the pitch bounded between specified limits Simulation results are provided to show the efficacy of the controllers using realistic data

Maneuver-based motion planning for nonlinear systems with symmetries

Abstract: In this paper, we introduce an approach for the efficient solution of motion-planning problems for time-invariant dynamical control systems with symmetries, such as mobile robots and autonomous vehicles, under a variety of differential and algebraic constraints on the state and on the control inputs. Motion plans are described as the concatenation of a number of well-defined motion primitives, selected from a finite library. Rules for the concatenation of primitives are given in the form of a regular language, defined through a finite-state machine called a Maneuver Automaton. We analyze the reachability properties of the language, and present algorithms for the solution of a class of motion-planning problems. In particular, it is shown that the solution of steering problems for nonlinear dynamical systems with symmetries and invariant constraints can be reduced to the solution of a sequence of kinematic inversion problems. A detailed example of the application of the proposed approach to motion planning for a small aerobatic helicopter is presented.

Differential-drive in-pipe robot for moving inside urban gas pipelines

Abstract: Pipelines for the urban gas-supply system require a robot possessing outstanding mobility and advanced control algorithms, since they are configured with various pipeline elements, such as straight pipelines, elbows, and branches. We present a comprehensive work for moving inside underground urban gas pipelines with a miniature differential-drive in-pipe robot, called the Multifunctional Robot for IN-pipe inSPECTion (MRINSPECT) IV. MRINSPECT IV has been developed for the inspection of urban gas pipelines with a nominal 4-in inside diameter. The mechanism for steering with differential-drive wheels, arranged three-dimensionally, allows it to easily adapt to most of the existing configurations of pipelines, as well as providing excellent mobility during navigation. After carrying out analysis for fittings in pipelines, mathematical descriptions of their geometries are presented, which make it possible to estimate the movement patterns of the robot while passing through the fittings. Also, we propose a method of controlling the robot by modulating speeds of driving wheels that is applicable without sophisticated sensory information. To confirm the effectiveness of the proposed method, experiments are performed, and supplementary considerations on the design of the in-pipe robot are discussed.

Hierarchical SLAM: real-time accurate mapping of large environments

Abstract: In this paper, we present a hierarchical mapping method that allows us to obtain accurate metric maps of large environments in real time. The lower (or local) map level is composed of a set of local maps that are guaranteed to be statistically independent. The upper (or global) level is an adjacency graph whose arcs are labeled with the relative location between local maps. An estimation of these relative locations is maintained at this level in a relative stochastic map. We propose a close to optimal loop closing method that, while maintaining independence at the local level, imposes consistency at the global level at a computational cost that is linear with the size of the loop. Experimental results demonstrate the efficiency and precision of the proposed method by mapping the Ada Byron building at our campus. We also analyze, using simulations, the precision and convergence of our method for larger loops.

A multilevel relaxation algorithm for simultaneous localization and mapping

Abstract: This paper addresses the problem of simultaneous localization and mapping (SLAM) by a mobile robot. An incremental SLAM algorithm is introduced that is derived from multigrid methods used for solving partial differential equations. The approach improves on the performance of previous relaxation methods for robot mapping, because it optimizes the map at multiple levels of resolution. The resulting algorithm has an update time that is linear in the number of estimated features for typical indoor environments, even when closing very large loops, and offers advantages in handling nonlinearities compared with other SLAM algorithms. Experimental comparisons with alternative algorithms using two well-known data sets and mapping results on a real robot are also presented.

Revisiting trilateration for robot localization

Abstract: Locating a robot from its distances, or range measurements, to three other known points or stations is a common operation, known as trilateration. This problem has been traditionally solved either by algebraic or numerical methods. An approach that avoids the direct algebrization of the problem is proposed here. Using constructive geometric arguments, a coordinate-free formula containing a small number of Cayley-Menger determinants is derived. This formulation accommodates a more thorough investigation of the effects caused by all possible sources of error, including round-off errors, for the first time in this context. New formulas for the variance and bias of the unknown robot location estimation, due to station location and range measurements errors, are derived and analyzed. They are proved to be more tractable compared with previous ones, because all their terms have geometric meaning, allowing a simple analysis of their asymptotic behavior near singularities.

Electroencephalogram-based control of an electric wheelchair

Abstract: This paper presents a study on electroencephalogram (EEG)-based control of an electric wheelchair. The objective is to control the direction of an electric wheelchair using only EEG signals. In other words, this is an attempt to use brain signals to control mechanical devices such as wheelchairs. To achieve this goal, we have developed a recursive training algorithm to generate recognition patterns from EEG signals. Our experimental results demonstrate the utility of the proposed recursive training algorithm and the viability of accomplishing direction control of an electric wheelchair by only EEG signals.

Swarm aggregations using artificial potentials and sliding-mode control

Abstract: In this paper, we consider a control strategy of multiagent systems, or simply, swarms, based on artificial potential functions and the sliding-mode control technique. First, we briefly discuss a "kinematic" swarm model in n-dimensional space introduced in an earlier paper. In that model, the interindividual interactions are based on artificial potential functions, and the motion of the individuals is along the negative gradient of the combined potential. After that, we consider a general model for vehicle dynamics of each agent (swarm member), and use sliding-mode control theory to force their motion to obey the dynamics of the kinematic model. In this context, the results for the initial model serve as a "proof of concept" for multiagent coordination and control (swarm aggregation), whereas the present results serve as a possible implementation method for engineering swarms with given vehicle dynamics. The presented control scheme is robust with respect to disturbances and system uncertainties.

Point-based and region-based image moments for visual servoing of planar objects

Abstract: Moments are generic (and usually intuitive) descriptors that can be computed from several kinds of objects, defined either from closed contours or from a set of points. In this paper, we present improvements in image-based visual servo using image moments. First, the analytical form of the interaction matrix related to the moments computed from a set of coplanar points is derived, and we show that it is different from the form obtained previously, using coplanar closed contours. Six visual features are selected to design a decoupled control scheme when the object is parallel to the image plane. This nice property is then generalized to the case where the desired object position is not parallel to the image plane. Finally, experimental results are presented to illustrate the validity of our approach and its robustness, with respect to modeling errors.

A convergent dynamic window approach to obstacle avoidance

Abstract: The dynamic window approach (DWA) is a well-known navigation scheme developed by Fox et al. and extended by Brock and Khatib. It is safe by construction, and has been shown to perform very efficiently in experimental setups. However, one can construct examples where the proposed scheme fails to attain the goal configuration. What has been lacking is a theoretical treatment of the algorithm's convergence properties. Here we present such a treatment by merging the ideas of the DWA with the convergent, but less performance-oriented, scheme suggested by Rimon and Koditschek. Viewing the DWA as a model predictive control (MPC) method and using the control Lyapunov function (CLF) framework of Rimon and Koditschek, we draw inspiration from an MPC/CLF framework put forth by Primbs to propose a version of the DWA that is tractable and convergent.

Enhanced stiffness modeling, identification and characterization for robot manipulators

Abstract: This paper presents the enhanced stiffness modeling and analysis of robot manipulators, and a methodology for their stiffness identification and characterization. Assuming that the manipulator links are infinitely stiff, the enhanced stiffness model contains: 1) the passive and active stiffness of the joints and 2) the active stiffness created by the change in the manipulator configuration, and by external force vector acting upon the manipulator end point. The stiffness formulation not accounting for the latter is known as conventional stiffness formulation, which is obviously not complete and is valid only when: 1) the manipulator is in an unloaded quasistatic configuration and 2) the manipulator Jacobian matrix is constant throughout the workspace. The experimental system considered in this study is a Motoman SK 120 robot manipulator with a closed-chain mechanism. While the deflection of the manipulator end point under a range of external forces is provided by a high precision laser measurement system, a wrist force/torque sensor measures the external forces. Based on the experimental data and the enhanced stiffness model, the joint stiffness values are first identified. These stiffness values are then used to prove that conventional stiffness modeling is incomplete. Finally, they are employed to characterize stiffness properties of the robot manipulator. It has been found that although the component of the stiffness matrix differentiating the enhanced stiffness model from the conventional one is not always positive definite, the resulting stiffness matrix can still be positive definite. This follows that stability of the stiffness matrix is not influenced by this stiffness component. This study contributes to the previously reported work from the point of view of using the enhanced stiffness model for stiffness identification, verification and characterization, and of new experimental results proving that the conventional stiffness matrix is not complete and is valid under certain assumptions.

Motion planning for multitarget surveillance with mobile sensor agents

Abstract: In the surveillance of multiple targets by mobile sensor agents (MSAs), system performance relies greatly on the motion-control strategy of the MSAs. This paper investigates the motion-planning problem for a limited resource of M MSAs in an environment of N targets (M

Discrete abstractions for robot motion planning and control in polygonal environments

Abstract: In this paper, we present a computational framework for automatic generation of provably correct control laws for planar robots in polygonal environments. Using polygon triangulation and discrete abstractions, we map continuous motion planning and control problems, specified in terms of triangles, to computationally inexpensive problems on finite-state-transition systems. In this framework, discrete planning algorithms in complex environments can be seamlessly linked to automatic generation of feedback control laws for robots with underactuation constraints and control bounds. We focus on fully actuated kinematic robots with velocity bounds and (underactuated) unicycles with forward and turning speed bounds.

How UGVs physically fail in the field

Abstract: This paper presents a detailed look at how unmanned ground vehicles (UGVs) fail in the field using information from 10 studies and 15 different models in Urban Search and Rescue or military field applications. One explores failures encountered in a limited amount of time in a real crisis (World Trade Center rescue response). Another covers regular use of 13 robots over two years. The remaining eight studies are field tests of robots performed by the Test and Evaluation Coordination Office at Fort Leonard Wood. A novel taxonomy of UGV failures is presented which categorizes failures based on the cause (physical or human), its impact, and its repairability. Important statistics are derived and illustrative examples of physical failures are examined using this taxonomy. Reliability in field environments is low, between 6 and 20 hours mean time between failures. For example, during the PANTHER study (F. Cook, 1997) 35 failures occurred in 32 days. The primary cause varies: one study showed 50% of failures caused by effectors; another study showed 54% of failures occurred in the control system. Common causes are: unstable control systems, platforms designed for a narrow range of conditions, limited wireless communication range, and insufficient bandwidth for video-based feedback.

Evolutionary route planner for unmanned air vehicles

Abstract: Based on evolutionary computation, a novel real-time route planner for unmanned air vehicles is presented. In the evolutionary route planner, the individual candidates are evaluated with respect to the workspace so that the computation of the configuration space is not required. The planner incorporates domain-specific knowledge, can handle unforeseeable changes of the environment, and take into account different kinds of mission constraints such as minimum route leg length and flying altitude, maximum turning angle, and fixed approach vector to goal position. Furthermore, the novel planner can be used to plan routes both for a single vehicle and for multiple ones. With Digital Terrain Elevation Data, the resultant routes can increase the surviving probability of the vehicles using the terrain masking effect.

Cable suspended planar robots with redundant cables: controllers with positive tensions

Abstract: Cable-suspended robots are structurally similar to parallel actuated robots but with the fundamental difference that cables can only pull the end-effector but not push it. From a scientific point of view, this feature makes feedback control of cable-suspended robots more challenging than their counterpart parallel-actuated robots. In the case with redundant cables, feedback control laws can be designed to make all tensions positive while attaining desired control performance. This paper presents approaches to design positive tension controllers for cable suspended robots with redundant cables. Their effectiveness is demonstrated through simulations and experiments on a three degree-of-freedom cable suspended robots.

Contact impedance estimation for robotic systems

Abstract: In this paper, the problem of online estimation of the mechanical impedance during the contact of a robotic system with an unknown environment is considered. This problem is of great interest when controlling a robot in an unstructured and unknown environment, such as in telemanipulation tasks, since it can be easily shown that the exploitation of the knowledge of the mechanical properties of the environment can greatly improve the performance of the robotic system. In particular, a single-point contact is considered, and the (nonlinear) Hunt-Crossley model is taken into account, instead of the classical (linear) Kelvin-Voigt model. Indeed, the former achieves a better physical consistency and also allows describing the behavior of soft materials. Finally, the online estimation algorithm is described and experimental results are presented and discussed.

Active filtering of physiological motion in robotized surgery using predictive control

Abstract: This work presents a predictive-control approach to active mechanical filtering of complex, periodic motions of organs induced by respiration or heart beating in robotized surgery. Two different predictive-control schemes are proposed for the compensation of respiratory motions or cardiac motions. For respiratory motions, the periodic property of the disturbance has been included into the input-output model of the controlled system so as to have the robotic system learn and anticipate perturbation motions. A new cost function is proposed for the unconstrained generalized predictive controller (GPC), where reference tracking is decoupled from the rejection of predictable periodic motions. Cardiac motions are more complex, since they are the combination of two periodic nonharmonic components. An adaptive disturbance predictor is proposed which outputs future predicted disturbance values. These predicted values are used to anticipate the disturbance by using the predictive feature of a regular GPC. Experimental results are presented on a laboratory testbed and in vivo on pigs. They demonstrate the effectiveness of the two proposed methods to compensate complex physiological motion.

Robust vision-based localization by combining an image-retrieval system with Monte Carlo localization

Abstract: In this paper, we present a vision-based approach to mobile robot localization that integrates an image-retrieval system with Monte Carlo localization. The image-retrieval process is based on features that are invariant with respect to image translations and limited scale. Since it furthermore uses local features, the system is robust against distortion and occlusions, which is especially important in populated environments. To integrate this approach with the sample-based Monte Carlo localization technique, we extract for each image in the database a set of possible viewpoints using a two-dimensional map of the environment. Our technique has been implemented and tested extensively. We present practical experiments illustrating that our approach is able to globally localize a mobile robot, to reliably keep track of the robot's position, and to recover from localization failures. We furthermore present experiments designed to analyze the reliability and robustness of our approach with respect to larger errors in the odometry.

How to keep from falling forward: elementary swing leg action for passive dynamic walkers

Abstract: Stability control for walking bipeds has been considered a complex task Even two-dimensional fore-aft stability in dynamic walking appears to be difficult to achieve In this paper we prove the contrary, starting from the basic belief that in nature stability control must be the sum of a number of very simple rules We study the global stability of the simplest walking model by determining the basin of attraction of the Poincare/spl acute/ map of this model This shows that the walker, although stable, can only handle very small disturbances It mostly falls, either forward or backward We show that it is impossible for any form of swing leg control to solve backward falling For the problem of forward falling, we devise a simple but very effective rule for swing leg action: "You will never fall forward if you put your swing leg fast enough in front of your stance leg In order to prevent falling backward the next step, the swing leg shouldn't be too far in front" The effectiveness of this rule is demonstrated with our prototype "Mike"

Randomized pursuit-evasion in a polygonal environment

Abstract: This paper contains two main results. First, we revisit the well-known visibility-based pursuit-evasion problem, and show that in contrast to deterministic strategies, a single pursuer can locate an unpredictable evader in any simply connected polygonal environment, using a randomized strategy. The evader can be arbitrarily faster than the pursuer, and it may know the position of the pursuer at all times, but it does not have prior knowledge of the random decisions made by the pursuer. Second, using the randomized algorithm, together with the solution to a problem called the "lion and man problem" as subroutines, we present a strategy for two pursuers (one of which is at least as fast as the evader) to quickly capture an evader in a simply connected polygonal environment. We show how this strategy can be extended to obtain a strategy for a polygonal room with a door, two pursuers who have only line-of-sight communication, and a single pursuer (at the expense of increased capture time).

Effects of position quantization and sampling rate on virtual-wall passivity

Abstract: The "virtual wall" is the most common building block used in constructing haptic virtual environments. A virtual wall is typically based on a simple spring model, with unilateral constraints that allow the user to make and break contact with a surface. There are a number of factors (sample-and-hold, device dynamics, sensor quantization, etc.) that cause virtual walls to demonstrate active (nonpassive) behavior, destroying the illusion of reality. In this paper, we find an explicit upper bound on virtual wall stiffness that is a necessary and sufficient condition for virtual wall passivity. We consider a haptic display that can be modeled as a mass with Coulomb-plus-viscous friction, being acted upon by two external forces: an actuator and a human user. The system is equipped with only one sensor, an optical encoder measuring the position of the mass. We explicitly model the effects of position resolution, which has not been done in previous work. We make no assumptions about the human user, and we consider arbitrary constant sampling rates. The main result of our analysis is a necessary and sufficient condition for passivity that relies on the Coulomb friction in the haptic device, as well as the encoder resolution. We experimentally verify our results with a one-degree-of-freedom haptic display, and find that the system can display nonpassive behavior in two decoupled modes that are predicted by the necessary and sufficient condition. One mode represents instability, while the other mode results in active tactile sensations.

Somatosensory computation for man-machine interface from motion-capture data and musculoskeletal human model

Abstract: We discuss the computation of somatosensory information from motion-capture data. The efficient computational algorithms previously developed by the authors for multibody systems, such as humanoid robots, are applied to a musculoskeletal model of the human body. The somatosensory information includes tension, length, and velocity of the muscles, tension of the tendons and ligaments, pressure of the cartilages, and stress of the bones. The inverse dynamics of the musculoskeletal human model is formulated as an optimization problem subject to equality and inequality conditions. We analyzed the solutions obtained by linear and quadratic programming methods, and showed that linear programming has better performance. The technological development aims to define a higher dimensional man-machine interface and to open the door to the cognitive-level communication of humans and machines.

Sampling-based roadmap of trees for parallel motion planning

Abstract: This paper shows how to effectively combine a sampling-based method primarily designed for multiple-query motion planning [probabilistic roadmap method (PRM)] with sampling-based tree methods primarily designed for single-query motion planning (expansive space trees, rapidly exploring random trees, and others) in a novel planning framework that can be efficiently parallelized. Our planner not only achieves a smooth spectrum between multiple-query and single-query planning, but it combines advantages of both. We present experiments which show that our planner is capable of solving problems that cannot be addressed efficiently with PRM or single-query planners. A key advantage of our planner is that it is significantly more decoupled than PRM and sampling-based tree planners. Exploiting this property, we designed and implemented a parallel version of our planner. Our experiments show that our planner distributes well and can easily solve high-dimensional problems that exhaust resources available to single machines and cannot be addressed with existing planners.

Roadmap-based motion planning in dynamic environments

Abstract: In this paper, a new method is presented for motion planning in dynamic environments, that is, finding a trajectory for a robot in a scene consisting of both static and dynamic, moving obstacles. We propose a practical algorithm based on a roadmap that is created for the static part of the scene. On this roadmap, an approximately time-optimal trajectory from a start to a goal configuration is computed, such that the robot does not collide with any moving obstacle. The trajectory is found by performing a two-level search for a shortest path. On the local level, trajectories on single edges of the roadmap are found using a depth-first search on an implicit grid in state-time space. On the global level, these local trajectories are coordinated using an A/sup */-search to find a global trajectory to the goal configuration. The approach is applicable to any robot type in configuration spaces with any dimension, and the motions of the dynamic obstacles are unconstrained, as long as they are known beforehand. The approach has been implemented for both free-flying and articulated robots in three-dimensional workspaces, and it has been applied to multirobot motion planning, as well. Experiments show that the method achieves interactive performance in complex environments.

Internal Preload Control of Redundantly Actuated Parallel Manipulators—Its Application to Backlash Avoiding Control

Abstract: Redundant actuation of parallel manipulators can lead to internal forces without generating end-effector forces (preload). Preload can be controlled in order to prevent backlash during the manipulator motion. Such control is based on the inverse dynamics. The general solution of the inverse dynamics of redundantly actuated parallel manipulators is given. For the special case of simple overactuation an explicit solution is derived in terms of a single preload parameter. With this formulation a computational efficient open-loop preload control is developed and applied to the elimination of backlash. Its simplicity makes it applicable in real-time applications. Results are given for a planar 4RRR manipulator and a spatial heptapod.

Sampled data systems passivity and discrete port-Hamiltonian systems

Abstract: In this paper, we present a novel way to approach the interconnection of a continuous and a discrete time physical system first presented in . This is done in a way which preserves passivity of the coupled system independently of the sampling time T. This strategy can be used both in the field of telemanipulation, for the implementation of a passive master/slave system on a digital transmission line with varying time delays and possible loss of packets (e.g., the Internet), and in the field of haptics, where the virtual environment should 'feel' like a physical equivalent system.