Showing papers on "Obstacle avoidance published in 1999"

High-speed navigation using the global dynamic window approach

Abstract: Many applications in mobile robotics require the safe execution of a collision-free motion to a goal position. Planning approaches are well suited for achieving a goal position in known static environments, while real-time obstacle avoidance methods allow reactive motion behavior in dynamic and unknown environments. This paper proposes the global dynamic window approach as a generalization of the dynamic window approach. It combines methods from motion planning and real-time obstacle avoidance to result in a framework that allows robust execution of high-velocity, goal-directed reactive motion for a mobile robot in unknown and dynamic environments. The global dynamic window approach is applicable to nonholonomic and holonomic mobile robots.

The NavChair Assistive Wheelchair Navigation System

Abstract: The NavChair Assistive Wheelchair Navigation System is being developed to reduce the cognitive and physical requirements of operating a power wheelchair for people with wide ranging impairments that limit their access to powered mobility. The NavChair is based on a commercial wheelchair system with the addition of a DOS-based computer system, ultrasonic sensors, and an interface module interposed between the joystick and power module of the wheelchair. The obstacle avoidance routines used by the NavChair in conjunction with the ultrasonic sensors are modifications of methods originally used in mobile robotics research. The NavChair currently employs three operating modes: general obstacle avoidance, door passage, and automatic wall following. Results from performance testing of these three operating modes demonstrate their functionality. In additional to advancing the technology of smart wheelchairs, the NavChair has application to the development and testing of "shared control" systems where a human and machine share control of a system and the machine can automatically adapt to human behaviors.

Vehicle safety running control system

Abstract: A system for controlling running safety of a vehicle having at least a brake, a steering mechanism manipulated by a vehicle operator, a laser radar for detecting an obstacle present ahead on a course of travel of the vehicle, and a brake actuator mechanism actuating the brake independently of the vehicle operator manipulation. In the system, a first threshold value (defined in terms of relative distance between the vehicle and the obstacle) for avoiding contact with the obstacle by steering and a second threshold value for avoiding contact by operating the brake actuator mechanism are determined and are compared with the detected relative distance. When the detected relative distance is less than the first threshold value, the brake actuator mechanism is immediately operated to generate a relatively small deceleration, thereby enabling effective obstacle avoidance to well meet the intention and desires of the vehicle operator, without causing a problem of interference with the steering of the vehicle operator, while preventing the control accuracy from being degraded.

An intelligent mobile vehicle navigator based on fuzzy logic and reinforcement learning

Abstract: In this paper, an alternative training approach to the EEM-based training method is presented and a fuzzy reactive navigation architecture is described. The new training method is 270 times faster in learning speed; and is only 4% of the learning cost of the EEM method. It also has very reliable convergence of learning; very high number of learned rules (98.8%); and high adaptability. Using the rule base learned from the new method, the proposed fuzzy reactive navigator fuses the obstacle avoidance behaviour and goal seeking behaviour to determine its control actions, where adaptability is achieved with the aid of an environment evaluator. A comparison of this navigator using the rule bases obtained from the new training method and the EEM method, shows that the new navigator guarantees a solution and its solution is more acceptable.

Ultrasonic potential field sensor for obstacle avoidance

Abstract: We introduce an ultrasonic sensor system that measures artificial potential fields (APFs) directly. The APF is derived from the traveling-times of the transmitted pulses. Advantages of the sensor are that it needs only three transducers, that its design is simple, and that it measures a quantity that can be used directly for simple navigation, such as collision avoidance.

Placing a robot manipulator amid obstacles for optimized execution

Abstract: This paper presents an efficient algorithm for optimizing the base location of a robot manipulator in an environment cluttered with obstacles, in order to execute specified tasks as fast as possible. The algorithm uses randomized motion planning techniques and exploits geometric "coherence" in configuration space to achieve fast computation. The performance of the algorithm is demonstrated on both synthetic examples and real-life CAD data from the automotive industry. The computation time ranges from under a minute for simple problems to a few minutes for more complex ones.

Coordination of reaching and grasping by capitalizing on obstacle avoidance and other constraints.

Abstract: Reaching and grasping an object can be viewed as the solution of a multiple-constraint satisfaction problem. The constraints include contact with the object with the appropriate effectors in the correct positions as well as generation of a collision-free trajectory. We have developed a computational model that simulates reaching and grasping based on these notions. The model, rendered as an animation program, reproduces many basic features of the kinematics of human reaching and grasping behavior. The core assumptions of the model are: (1) tasks are defined by flexibly organized constraint hierarchies; (2) manual positioning acts, including prehension acts, are first specified with respect to goal postures and then are specified with respect to movements towards those goal postures; (3) goal postures are found by identifying the stored posture that is most promising for the task, as determined by the constraint hierarchy, and then by generating postures that are more and more dissimilar to the most-promising stored posture until a deadline is reached, at which time the best posture that was found during the search is defined as the goal posture; (4) depending on when the best posture was encountered in the search, the deadline for the search in the next trial is either increased or decreased; (5) specification of a movement to the goal posture begins with straight-line interpolation in joint space between the starting posture and goal posture; (6) if an internal simulation of this default movement suggests that it will result in collision with an obstacle, the movement can be reshaped until an acceptable movement is found or until time runs out; (7) movement reshaping occurs by identifying a via posture that serves as a body position to which the actor moves from the starting posture and then back to the starting posture, while simultaneously making the main movement from the starting posture to the goal posture; (8) the via posture is identified using the same posture-generating algorithm as used to identify the goal posture. These processes are used both for arm positioning and, with some elaboration, for prehension. The model solves a number of problems with an earlier model, although it leaves some other problems unresolved.

Real-time Single-workstation Obstacle Avoidance Using Only Wide-field Flow Divergence

Abstract: A real-time robot vision system is described which uses only the divergence of the optical flow field for both steering control and collision detection. The robot has wandered about the lab at 20 cm/s for as long as 26 minutes without collision. The entire system is implemented on a single ordinary UNIX workstation without the benefit of real-time operating system support. Dense optical flow data are calculated in real-time across the entire wide-angle image. The divergence of this optical flow field is calculated everywhere and used to control steering and collision behavior. Divergence alone has proven sufficient for steering past objects and detecting imminent collision. The major contribution is the demonstration of a simple, robust, minimal system that uses flow-derived measures to control steering and speed to avoid collision in real time for extended periods. Such a system can be embedded in a general, multi-level perception/control system.

Safeguarded Teleoperation for Lunar Rovers: From Human Factors to Field Trials

Abstract: In this paper we present recent advances in developing and validating the safeguarded teleoperation approach to time-delayed remote driving. This approach shares control of the rover using a command fusion strategy: In benign situations, users remotely drive the rover; in hazardous situations, a safeguarding system running on-board the rover overwrites user commands to ensure vehicle safety. This strategy satisfies users, because it allows them to drive (except in hazardous situations), while maintaining the integrity of the rover and mission. We present results from experiments on untrained teleoperators with and without safeguarding, which reveal needs to be met by future user interfaces. We describe three technical advances in safeguarding: improving the accuracy of dead reckoning by a factor of 2, speeding up the controller by a factor of 18, and developing an area-based rather than a path-based obstacle avoidance planner in order to circumvent map merging problems. Finally, we discuss a field trial validating the approach in a 10 km traverse, demonstrating the effectiveness of safeguarding, even with malicious drivers.

Automatic running support system

Abstract: PROBLEM TO BE SOLVED: To enable each vehicle to safely and smoothly run autonomously by making a road-side controller and each vehicle requiring avoidance perform the most suitable obstacle avoiding operation in cooperation with each other. SOLUTION: Information of an obstacle detected by a running vehicle MS1 and information of the obstacle detected by a road-side sensor LS are exchanged through an road-vehicle communication system consisting of a road-side machine BSi and a radio machine on the vehicle, and a centralized base station CS2 generates avoidance indication information based on both detected information. The avoidance indication information is reported to vehicles MS1 and MS2 requiring the avoiding operation through the road-vehicle communication system, and thus the vehicle MS1 performs the avoiding operation.

Elastic Strips: A Framework for Integrated Planning and Execution

Abstract: The execution of robotic tasks in dynamic, unstructured environments requires the generation of motion plans that respect global constraints imposed by the task while avoiding collisions with stationary, moving, and unforeseen obstacles. This paper presents the elastic strip framework, which addresses this problem by integrating global motion planning methods with a reactive motion execution approach. To maintain a collision-free trajectory, a given motion plan is incrementally modified to reflect changes in the environment. This modification can be performed without suspending task behavior. The elastic strip framework is computationally efficient and can be applied to robots with many degrees of freedom. The paper also presents experimental results obtained by the implementation of this framework on the the Stanford Mobile Manipulator.

Obstacle avoidance control system for vehicle

Abstract: The avoidance of an obstacle by a vehicle is enhanced by effective balancing an automatic braking operation and a turnability increasing control operation assisting in a steering operation of the vehicle whereby the obstacle avoiding capability is enhanced to the maximum. If a vehicle is being automatically controlled and the steering operation is carried out by the driver and if it is determined an obstacle can be avoided by a turnability increasing control operation, and if an avoiding space exists in a direction of turning of the vehicle, the turnability increasing control operation is carried out to perform the avoidance of the obstacle by the steering operation. If no avoiding space exists in the direction of turning of the vehicle, the avoidance of the obstacle by the steering operation is not performed, and a stability increasing control operation is carried out to effectively perform the avoidance of the obstacle by the automatic braking operation.

Reactive navigation in dynamic environment using a multisensor predictor

Abstract: A reactive navigation system for an autonomous mobile robot in unstructured dynamic environments is presented. The motion of moving obstacles is estimated for robot motion planning and obstacle avoidance. A multisensor-based obstacle predictor is utilized to obtain obstacle-motion information. Sensory data from a CCD camera and multiple ultrasonic range finders are combined to predict obstacle positions at the next sampling instant. A neural network, which is trained off-line, provides the desired prediction on-line in real time. The predicted obstacle configuration is employed by the proposed virtual force based navigation method to prevent collision with moving obstacles. Simulation results are presented to verify the effectiveness of the proposed navigation system in an environment with multiple mobile robots or moving objects. This system was implemented and tested on an experimental mobile robot at our laboratory. Navigation results in real environment are presented and analyzed.

Improved Rover State Estimation in Challenging Terrain

Abstract: Given ambitious mission objectives and long delay times between command-uplink/data-downlink sessions, increased autonomy is required for planetary rovers. Specifically, NASA‘s planned 2003 and 2005 Mars rover missions must incorporate increased autonomy if their desired mission goals are to be realized. Increased autonomy, including autonomous path planning and navigation to user designated goals, relies on good quality estimates of the rover‘s state, e.g., its position and orientation relative to some initial reference frame. The challenging terrain over which the rover will necessarily traverse tends to seriously degrade a dead-reckoned state estimate, given severe wheel slip and/or interaction with obstacles. In this paper, we present the implementation of a complete rover navigation system. First, the system is able to adaptively construct semi-sparse terrain maps based on the current ground texture and distances to possible nearby obstacles. Second, the rover is able to match successively constructed terrain maps to obtain a vision-based state estimate which can then be fused with wheel odometry to obtain a much improved state estimate. Finally the rover makes use of this state estimate to perform autonomous real-time path planning and navigation to user designated goals. Reactive obstacle avoidance is also implemented for roaming in an environment in the absence of a user designated goal. The system is demonstrated in soft soil and relatively dense rock fields, achieving state estimates that are significantly improved with respect to dead reckoning alone (e.g., 0.38 m mean absolute error vs. 1.34 m), and successfully navigating in multiple trials to user designated goals.

Vehicle behavior control system

Abstract: A system for controlling behavior of a vehicle having a laser radar for detecting an obstacle present on a road on which the vehicle is traveling and operating the brake automatically to avoid contact with the obstacle, and having a power-assist steering actuator including an electric motor installed in the steering system. In the system, it is determined whether the vehicle is steered by the steering wheel as manipulated by the vehicle operator or the vehicle is steered by a force generated by the interplay between the tire and road due to the automatic braking and, when vehicle is steered by the force generated by the tire/road interplay, the electric motor of the steering actuator is controlled to drive in the direction to cancel the force, thereby preventing the vehicle behavior from degrading to deviate from the desired course of travel and preventing various disadvantages such as failure to achieve the desired obstacle detection necessary for an effective obstacle avoidance control.

Path planning of mobile robot using neural network

Abstract: In this paper, the authors present an effective method to achieve both obstacle-avoidance and target-tracking for an autonomous mobile robot in an indoor environment. They employ a wall following algorithm using neural network pattern recognition to avoid obstacles. An autonomous mobile robot reaches a given goal target by tracking algorithm. In case obstacles are detected by sonar sensors, an autonomous mobile robot avoids collision with obstacles by wall following algorithm. They propose a simple making method to avoid being trapped in a local minima which was a serious problem in local path planning. Simulation results using mobile robot demonstrate that the proposed algorithms are well suited to the obstacle-avoidance using wall-following and the path planning task for target-tracking.

Quasi-time-optimal motion planning of mobile platforms in the presence of obstacles

Abstract: This paper addresses a problem of optimal motion planning of mobile platforms amidst obstacles, considering the mobile platform dynamics. Due to nonholonomic constraints, actuator constraints, and state constraints by obstacle avoidance, the planning problem of mobile platform with two independently driven wheels is a complicated one. In this study, a dynamical model for the mobile platform is presented, including nonholonomic kinematic constraints. The idea of a path parameter is introduced to simplify the planning problem by considering the dynamics and nonholonomic constraints. Using the path parameter, the optimal motion planning problem is divided into two sub-problems: 1) time-optimization of trajectory along specified path, and 2) search for optimal path. Then two methods are proposed the solve the problems using the path parameter and parametrization by B-spline function. Finally, quasi-time-optimal solution for the original problem are planned by combining the two methods. Numerical examples show effectiveness of the motion planner.

Ensuring safe obstacle avoidance in a shared-control system

Abstract: This paper describes the Bremen Autonomous Wheelchair project. It shows that common static fire strategies for ultrasonic sensors are inherently unsafe and proposes a new adaptive fire strategy which delivers a complete coverage of the environment of the robot. Furthermore, a new obstacle avoidance approach for shared-control robotic systems is described in detail.

A Stochastic Map Building Method for Mobile Robot using 2-D Laser Range Finder

Abstract: This paper presents a stochastic map building method for mobile robot using a 2-D laser range finder. Unlike other methods that are based on a set of geometric primitives, the presented method builds a map with a set of obstacle regions. In building a map of the environment, the presented algorithm represents the obstacles with a number of stochastic obstacle regions, each of which is characterized by its own stochastic parameters such as mean and covariance. Whereas the geometric primitives based map sometimes does not fit well to sensor data, the presented method reliably represents various types of obstacles including those of irregular walls and sets of tiny objects. Their shapes and features are easily extracted from the stochastic parameters of their obstacle regions, and are used to develop reliable navigation and obstacle avoidance algorithms. The algorithm updates the world map in real time by detecting the changes of each obstacle region. Consequently, it is adequate for modeling the quasi-static environment, which includes occasional changes in positions of the obstacles rather than constant dynamic moves of the obstacles. The presented map building method has successfully been implemented and tested on the ARES-II mobile robot system equipped with a LADAR 2D-laser range finder.

Kinetic and energetic patterns for hindlimb obstacle avoidance during cat locomotion.

Abstract: The safe control of walking over different terrains requires appropriate adaptations in the dynamic and kinematic limb patterns To date, the study of locomotor dynamics in the cat has been confined to level, unobstructed walking The present study extends the work of Lavoie et al by applying linked segment analyses to estimate muscle contributions to torque and mechanical power at the hindlimb joints of two female cats during both unobstructed walking and obstacle avoidance Data during obstacle avoidance were analyzed both when the hindlimb led in clearance and was farthest from the obstacle, and when it trailed in clearance and was closest or near to the obstacle It was found that, in both the Far and Near obstructed conditions, the cats cleared the obstacles primarily by increasing the knee flexor torque already used during unobstructed gait Contributions from the hip and ankle muscle groups were more variable There was more emphasis on the hip extensors in mid to late stance, and the hip flexors generated a small amount of energy at paw-lift in the Far condition In the Near condition, the hip extensors were employed to control hip flexion We suggest that hip flexor generation power in mid-swing contributes to the clearance of the upcoming obstacle in the Far condition while, in the Near condition, hip flexion advances the already extended limb ahead of the obstacle The ankle was actively dorsiflexed in the Near condition but was maintained in extension in the Far condition The emphasis on active knee flexor control by the cat to avoid obstacles, as well as the dependence of ankle control on obstacle proximity, is similar to strategies seen for humans However, the knee flexor strategy is innate to the cat’s normal level walking control, whereas in humans active knee flexion at toe-off requires a reorganization from level, non-obstructed gait

Shortest path planning for a tethered robot or an anchored cable

Abstract: We consider the problem of planning shortest paths for a tethered robot with a finite length tether in a 2D environment with polygonal obstacles. We present an algorithm that runs in time O((k/sub l/+1)/sup 2/n/sup 4/) and finds the shortest path or correctly determines that none exists that obeys the constraints, where n is the number obstacle vertices, and k/sub l/ is the number loops in the initial configuration of the tether. The robot may cross its tether but nothing can cross obstacles, which cause the tether to bend. The algorithm can also be applied to planning a shortest path for the free end of an anchored cable.

Motion control in dynamic multi-robot environments

Abstract: This paper presents the motion control system used by CMUnited-98, the small-size league champion at RoboCup-98. The robotic soccer team consists of five robots that aim at achieving specific goals while navigating in a limited space shared with the five other opponent robots. We introduce our motion control algorithm, which allows a general differential-driven robot to accurately reach a target point with a desired orientation in an environment with multiple moving obstacles. We describe how the features of our motion controller help to build interesting and robust behaviors. We also briefly compare our system to other motion control techniques and include descriptions and illustrations of the performance of our fully-implemented motion control algorithm.

Short-Range Millimeter-Wave Radar Perception in a Polar Environment

Abstract: Autonomous vehicle operations in Antarctica challenge robotic perception. Flying ice and snow, changing illumination due to low sun angles and lack of contrast degrade stereo and laser sensing. Millimeter-wave radar offers remarkable advantages as a robotic perception modality because it is not as sensitive to the aforementioned conditions. Experiments with millimeter-wave radar in an Antarctic environment show minimal degradation of millimeter-wave sensing capabilities under blowing-snow conditions, as well as backscatter obtained from polar-terrain surfaces at grazing angles and detection of obstacles commonly found in polar areas. This paper presents issues relevant to short-range radar perception for a mobile robot in an Antarctic environment. The article describes the experiments and data-analysis procedures, and draws conclusions on the utility of millimeter-wave radar as a robotic sensor for obstacle avoidance and navigation in polar settings. Keywords–Millimeter-wave radar, millimeter-wave imaging, radar scattering, mobile robots, robot sensing.

Avoidance Manipulability for Redundant Manipulators

Abstract: This paper is concerned with avoidance manipulability of redundant manipulators for trajectory tracking and obstacle avoidance. Possibility of avoiding a collision with obstacles during tracking a desired hand trajectory is discussed with proposed avoidance matrix, avoidance manipulability ellipsoid and avoidance manipulability measure which are defined on each link constructing the manipulator except top link. A necessary and sufficient condition that the intermediate links can avoid obstacles in a work space is indicated that a dimension of range space of the avoidance matrix coincides with the one of the work space of the manipulator. That means the avoidance manipulability ellipsoid is expanded in the whole work space. Relations of the ellipsoids and factors which influence the shape, namely, a posture of the manipulator, redundant degree, a serial position of the intermediate link from base, and priorities of the avoiding tasks, are also analyzed. Finally we show analyzed results of avoidance possibility with the proposed avoidance manipulability by numerical examples.

Simultaneous stochastic mapping and localization

Abstract: In order to create truly autonomous mobile robots, the task of building an accurate map of an a priori unknown environment and concurrently using that map to navigate is a central problem. This thesis focuses on methods for performing concurrent mapping and localization using a feature-based approach. The concurrent mapping and localization problem is cast as a stochastic estimation problem. Based on Kalman filtering techniques, augmented stochastic mapping is introduced as a method for performing concurrent mapping and localization in realistic scenario simulations and experiments. The role of data association ambiguity, track initiation and track deletion in the presence of uncertainty and non-linear system dynamics are addressed. A novel approach is introduced to overcome the computational complexity inherent in mapping large areas with many features. Adaptive concurrent mapping and localization based on choosing the robot's action so as to maximize the expected Fisher information is introduced in order to achieve improved performance. Results from simulations, land and underwater experiments, and post-processing of oceanic data are presented to demonstrate the validity of the proposed approaches. Once a region is mapped and localization information is available, planning collision free trajectories from the current position to the goal position is important for reliable mobile robot operations. In this context, a novel path-planning algorithm based on harmonic potentials is introduced for performing path-planning and obstacle avoidance in dynamic environments. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

Fuzzy rule extraction for shooting action controller of soccer robot

Abstract: A fuzzy logic controller (FLC) for shooting action is proposed which is one of the fundamental actions for soccer robots. Shooting action is viewed as a posture control problem with such a constraint that the robot should not approach the ball so that the ball moves to the home team area. The FLC consists of two levels: one is the planner level that generates a path to the ball with obstacle avoidance. The other is the motion control level that outputs robot wheel velocities to follow the desired path given the robot's current posture. The effectiveness of the proposed scheme is verified by the real experiments.

A controller to perform a visually guided tracking task in a cluttered environment

Abstract: Presents a controller for driving a mobile robot towards a target in a cluttered environment The proposed method combines visual servoing techniques allowing the target to be tracked, with an obstacle avoidance strategy based on the information provided by a 2D laser range sensor Simulation results are presented at the end of the paper

Obstacle avoidance control for redundant manipulators using collidability measure

Abstract: We present a measure called collidability measure for obstacle avoidance control of redundant manipulators. Considering moving directions of manipulator links, the collidability measure is defined as the inverse of sum of predicted collision distances between links and obstacles. This measure is suitable for obstacle avoidance control since directions of moving links are as important as distances to obstacles. For dynamic redundancy resolution, null space control is utilized to avoid obstacles by minimizing the collidability measure. Also, by clarifying decomposition in the joint acceleration level, we present a simple dynamic control law with bounded joint torques which guarantees tracking of a given end-effector trajectory and improves a kinematic cost function such as collidability measure. Simulation results are presented to illustrate the effectiveness of the proposed algorithm.

Non-linear dynamical system approach to behavior modeling

Abstract: We present a dynamic systems approach to modeling and generating low-level behaviors for autonomous agents Such behaviors include real-time target tracking and obstacle avoidance in time-varying environments The novelty of the method lies on the integration of distinct non-linear dynamic systems to model the agent's interaction with the environment An angular velocity control dynamic system guides the agent's direction angle, while another dynamic system selects the environmental input that will be used in the control system The agent interacts with the environment through its knowledge of the position of stationary and moving objects In our system agents automatically avoid stationary and moving obstacles to reach the desired target(s) This approach allows us to prove the stability conditions that result in a principled methodology for the computation of the system's dynamic parameters We present a variety of real-time simulations that illustrate the power of our approach