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.

Abstract: In this paper a multi-joint robot for sewer inspection tasks is presented. In order to increase the operating scope the robot has been designed to run round or over obstacles, to follow sewage branches and is operated with no wire attached to it. As a result of the wireless approach the robot has to carry an energy resource and must be abbe to act autonomously. In this paper we give a short description of the mechanical design and the electronic components used. Then we describe the control system and show sequences and results of in-pipe experiments.

Abstract: An obstacle avoidance system, apparatus, and method is described suitable for use on autonomously guided or man-in-the-loop guided vehicles such as aircraft, missiles, cars, and other types of vehicles. The system provides guidance instructions in the situation where the vehicle encounters an obstacle either directly or indirectly in its path while traveling to a desired destination or where vehicles are traveling in formation. The system can be applied not only to obstacle avoidance but also to trajectory shaping by defining obstacles, operational boundaries and/or threats which influence the trajectory of the vehicle.

Abstract: This paper describes how fuzzy control can be applied to a sonar-based mobile robot. Behavior-based fuzzy control for HelpMate behaviors was designed using sonar sensors. The fuzzy controller provides a mechanism for combining sensor data from all sonar sensors which present different information. The behavior-based approach is implemented as an individual high priority behavior. The highest level behavior is called the task-oriented behavior, which consists of two subtasks, wall following and goal seeking. The middle level behavior is obstacle avoidance. The lowest level is an emergency behavior. Each behavior was built as an atomic agent based on the intelligent machine architecture (IMA). The results demonstrate that each behavior works correctly. The HelpMate robot can follow the wall, go to the goal, and avoid obstacles detected by the sonar sensors.

Abstract: In the navigation of an autonomous vehicle, tracking and avoidance of the obstacles presents an interesting problem as this involves the integration of the vision and the motion systems. In an unstructured environment, the problem becomes much more severe as the obstacles have to be clearly recognized for any decisive action to be taken. In this paper, we discuss a solution to detection and avoidance of simulated potholes in the path of an autonomous vehicle operating in an unstructured environment. Pothole avoidance may be considered similar to other obstacle avoidance except that the potholes are depressions rather than extrusions form a surface. A non-contact vision approach has been taken since potholes usually are significantly different visually from a background surface. Large potholes more than 2 feet in diameter will be detected. Furthermore, only white potholes will be detected on a background of grass, asphalt, sand or green painted bridges. The signals from the environment are captured by the vehicle's vision systems and pre-processed appropriately. A histogram is used to determine a brightness threshold to determine if a pothole is within the field of view. Then, a binary image is formed. Regions are then detected in the binary image. Regions that have a diameter close to 2 feet and a ratio of circumference to diameter close to pi are considered potholes. The neuro-fuzzy logic controller where navigational strategies are evaluated uses these signals to decide a final course of navigation. The primary significance of the solution is that it is interfaced seamlessly into the existing central logic controller. The solution can also be easily extended to detect and avoid any two dimensional shape.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Abstract: We present an efficient obstacle avoidance control algorithm for redundant manipulators using a new measure called collidability measure. Considering moving directions of manipulator links, the collidability measure is defined as the sum of inverse of predicted collision distances between links and obstacles: This measure is suitable for obstacle avoidance since directions of moving links are as important as distances to obstacles. For kinematic or dynamic redundancy resolution, null space control is utilized to avoid obstacles by minimizing the collidability measure: We present a velocity-bounded kinematic control law which allows reasonably large gains to improve the system performance. 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.

Abstract: This paper deals with automatic target tracking in video and sonar subsea sequences, an essential capability for automating tasks currently performed by remotely operated vehicles under pilot control. We describe two trackers, one for video sequences, the other for sector scan sonar sequences. No assumptions are made about the images, scene, or motion observed. To illustrate applications, we report results of our systems for 3-D structure reconstruction and panoramic mosaic building from video sequences and describe in some detail our path planning and obstacle avoidance system using sonar sequences.

Abstract: The authors (1998) suggested a new class of intelligent motion controllers, called evolutionary, hybrid PDE-ODE controllers (EHPCs). A controller of such a class is designed for the special task of guiding an agent in a fully unknown environment to a target set along an obstacle-free trajectory. The authors briefly described an extension that would allow an EHPC to jointly condition a motion trajectory with both directional and region avoidance constraints. In this paper, an in-depth investigation of the proposed extension is provided. Also, mathematical proofs of both convergence, and the ability to enforce directional and region avoidance constraints are supplied.

Abstract: In this paper, the use of algebraic and trigonometric splines for the trajectory planning of robot manipulators is discussed. First, the two methods are analyzed and compared in detail; then, a strategy, which involves a combined use of the two schemes to perform sudden changes in a predefined trajectory (e.g. in case of obstacle avoidance) is proposed. Results show that the main interest in using trigonometric splines lies especially in the task of connecting two separate pieces of cubic splines, as overshoots are significantly reduced, although the continuity of velocity, acceleration and (in case) jerk is guaranteed.

Abstract: The main objective of this paper is to show the advantages of using the time Petri net formalism for specification, validation, and code generation in robot-control applications. To achieve this objective, the authors consider as application the development of a control system for a mobile robot with a rotating rangefinder laser sensor with two degrees of freedom to be used in navigation tasks with obstacle avoidance. It is shown how the use of the time Petri net formalism in the shole development cycle can fulfill the reliability requirement of real-time systems, make the system development easy and quick, strongly reduce the time for the testing and tuning phases and, therefore, reduce the development cost significantly. It allows verification of functional and temporal requirements, error detection in the early stages of the development cycle, and automatic code generation, avoiding coding mistakes. Experimental tests show that the theoretical results obtained from the analysis of formal system models match the real-time behavior of the robotic system.

Abstract: In this paper, two novel approaches to unmanned underwater vehicle path planning are presented The main idea of the first approach, referred to as Constrained Optimisation (CO) is to represent the free space of the workspace as a set of inequality constraints using vehicle configuration variables The second approach converts robot path planning into a Semi-infinite Constrained Optimisation (SCO) problem The function interpolation technique is adopted to satisfy the start and goal configuration requirements Mathematical foundations for Constructive Solid Geometry (CSG), Boolean operations and approximation techniques are also presented to reduce the number of constraints, and to avoid local minima The advantages of these approaches are that the mature techniques developed in optimisation theory which guarantee convergence, efficiency and numerical robustness can be directly applied to the robot path planning problem Simulation results have been presented

Abstract: This paper describes a system which robustly estimates motion, and the 3D structure of a rigid environment, as a stereo vision platform moves through it. The system can cope with any camera motion, and any scene structure and is successful even in the presence of large jumps in camera position between the capture of successive image pairs, and when point matching is ambiguous. The system was developed to provide robust obstacle avoidance for a partially sighted person. The process described attempts to maximise use of the abundant information present in a stereo sequence. Key features include the use of multiple stereo match hypotheses, efficient motion computation from three images, and the use of this motion to ensure reliable matching, and to eliminate multiple stereo matches. Points are reconstructed in 3D space and tracked in a static coordinate frame with a Kalman Filter. This results in good 3D scene reconstructions. Structure which is impossible to match with certainty is absent, rather than being incorrectly reconstructed. As a result, the system is appropriate for obstacle detection. The results of processing some indoor and outdoor scenes, are given in the paper, and practical issues are highlighted throughout.

Abstract: This paper presents an online planner for suboptimal obstacle avoidance. It generates near-shortest paths incrementally by avoiding obstacles optimally one at a time. In known environments, obstacles are avoided in an order determined by a global criterion. In unknown environments, obstacles are avoided as they are detected by on-board sensors. This avoidance strategy is guaranteed to reach the goal regardless of the order in which the obstacles are avoided. The method is demonstrated in several examples for an omnidirectional point robot moving among planar polygonal obstacles.

Abstract: A solution to the trajectory tracking problem for mobile manipulators is proposed, that allows for the base to be influenced by a reactive, obstacle avoidance behavior. Given a trajectory for the gripper to follow, a tracking algorithm for the manipulator is designed, and at the same time the base motions are generated in such a way that the base is coordinated with the gripper. Furthermore, it is shown that the method allows arbitrary upper and lower bounds on the gripper-base distance to be set and this can be achieved without introducing deadlocks into the system. The solution also ensures that the control effort, spent on slow base motions, is kept small.

Abstract: Our project has developed and studied high instrumentation technologies for mine detection and mine disposal using measuring equipment mounted on a six-legged teleoperated walking robots. This robot is called COMET-1 which is a full-autonomous obstacle avoidance robot or a semi-autonomous obstacle avoidance robot that requires the operator's intervention. When detecting a mine, the robot will lower each leg onto the ground safely and stably without stepping on a mine. For the simulations and experiments in the present study, the authors created a simulation model by attaching an optical proximity sensor on the foot of each leg and designed a walking algorithm using compliance control. Also, they verified the efficiency by means of walking experiments.

Abstract: Autonomous collision avoidance is necessary if Unmanned Aerial Vehicles (UAVs) are to "blacken the sky" in massed attacks, accompany manned fighters on combat missions, and transition civil airspace. These vehicles will, in some manner, have to "see and avoid" other aircraft. An automated air collision avoidance system will fulfill a part of this need. It will automatically maneuver an aircraft, at the last instant, to avoid an air-to-air collision. It will function in a manner similar to a pilot avoiding a collision. It is a system that must be reliable, verifiable, and partially redundant, forming the last line of defense against collisions. It must provide nuisance free operation and allow safe interoperability. The requirements for such a system will be discussed in detail. Of particular interest are criteria to enable a safe, nuisance free system that will have embedded rules of the road for all encounters. Autonomous control of unmanned aerial vehicles is a goal for the US Air Force in the future. However, flying multiple unmanned vehicles in the same tactical airspace with manned fighters presents very challenging problems. Autonomous collision avoidance is a necessary step in moving toward this goal.

Abstract: This paper introduces a nonlinear oscillator scheme to control autonomous mobile robots. The method is based on observations of a successful control mechanism used in nature, the Central Pattern Generator. Simulations were used to assess the performance of oscillator controller when used to implement several behaviors in an autonomous robot operating in a closed arena. A sequence of basic behaviors (random wandering, obstacle avoidance and light following) was coordinated in the robot to produce the higher behavior of foraging for light. The controller is explored in simulations and tests on physical robots. It is shown that the oscillator—based controller outperforms a reactive controller in the tasks of exploring an arena with irregular walls and in searching for light.

Abstract: We propose a behavior learning method based on Bayesian networks and experience of interaction between human and robots, which does not need a priori knowledge and can be applied to human-robot interaction models. In this method, the behavior learning based on interaction experience was established. However, developers must adjust initial sensor state of the Bayesian network according to the user preference. In this paper, we propose a new method of state space construction for user adaptation based on introspection of interaction experience using genetic algorithms. We also give two examples: 1) obstacle avoidance tasks for mobile robots; and 2) symbol grounding for natural language instruction, for realization of user's adaptation of human-robot interaction.

Abstract: A fuzzy logic controller (FLC) for mobile robots is designed in a hierarchical structure. The designed FLC consists of two levels: the planner level and the motion control level. The planner level generates a path to the destination with obstacle avoidance. The singleton outputs of the planner are obtained using line and arc methods. The lower motion control level calculates the robot's wheel velocity so as to follow the path generated by the planner as to the current robot posture. The fuzzy singleton outputs are obtained by heuristics and tuned by evolutionary programming. The applicability of the controller is demonstrated using a robot soccer system.

Abstract: Describes a vision system for obstacle detection in mobile robot navigation. The system uses an image processing board equipped with an MPEG motion estimation processor that calculates a robust optic-flow-like vector field in real-time. This field is then evaluated by algorithms running in software on the host PC. As the solutions to the general problem of structure and motion from optic flow are too instable for the use in this application, the typical constraints of mobile robotics are exploited, i.e. a reduced set of motion parameters and a known ground plane. Ego-motion can then be reconstructed with robust one dimensional methods. A new criterion for obstacles that copes well with the noise properties of the motion field is introduced. For vectors belonging to obstacles the 3D information is reconstructed allowing not only qualitative detection of obstacles but quantitative path planning.

Abstract: Physically-based simulation software is commonly used for developing and testing low-level robot control algorithms. In order to facilitate the development and evaluation of higher-level robot behaviors, broader-based simulations are needed. Examples include software for simulating 3D vision, motion planning for obstacle avoidance, and integrating vision and planning. In addition to modeling the general interaction between the robot and its environment, the software can be used as a graphical user interface for directly controlling or interacting with a robot operating in the real world. This paper describes our current efforts toward building a large-scale software simulation framework for the development and testing of high-level behaviors for humanoid robots. We view this as a potential useful tool for the visualization and development of robotic systems, as well as an interactive, task-level programming interface for robots.

Abstract: This paper describes an incremental evolutionary approach used in the development of a suitable neural controller for achieving robust obstacle avoidance behavior, which is then further fine-tuned towards a wall following one for a simple mobile robot. The incremental approach mainly involves an alteration of the environment in which the evolution takes place as well the fitness function used in the genetic algorithm. This approach has been seen to be more fruitful than a single direct approach. Interesting behaviors have evolved from this incremental approach.

Abstract: A robotic HMMWV (a.k.a. “humvee”) drives autonomously offroad at speeds up to 35 km/h (10 m/s, 20 mph). Key features of the implementation that enable driving at these speeds are (1) planning the next 20 m with dynamically feasible trajectories, and (2) increasing the lateral clearance to obstacles at higher speeds. Clothoid trajectories are used in planning the vehicle’s immediate path. The speed-indexed clearance requirement improves the safety margin for the vehicle over a range of speeds while retaining the ability to maneuver in close quarters when necessary.

Abstract: We describe a study on a teleoperated robot control system developed in the ART (Advanced Robotics and Teleoperation) Lab. at the University of Alberta. When using the system, a remote operator just needs a general-purpose computer with Internet connection and a World Wide Web (WWW) browser to remotely operate the robot through the Internet. A control architecture that combines computer and robot is constructed. This system is divided into two primary parts, the client part, which is executed on the remote operator's computer, and the server part, which resides on the server workstation in the ART Lab. The two parts are connected via the Internet. A graphical interface on the remote computer screen, showing the robot and its environment, enables the remote operator to send control commands to the robot. Communication coordination between the client and the server is developed using Java language. Since the real-time control through the Internet typically suffers from random time-delay and bandwidth constraints, many traditional control methods will suffer from stability and obstacle avoidance related issues. One approach to deal with the mentioned problems is to use event-based control methods for planning and control which have been successful in reducing the effects of the constraints by adopting a nontime based reference system in the control algorithm. We will apply this method in our Internet-based telerobotic systems. The nontime referenced action control scheme is used to deal with the unpredictable time-delays.

Abstract: Radar offers advantages as a robotic perception modality because it is not as vulnerable to the vacuum, dust, fog, rain, snow and light conditions found in construction, mining, agricultural and planetary-exploration environments. However radar has shortcomings such as a large footprint, sidelobes, specularity effects and limited range resolution—all of which result in poor environment maps. Evidence grids are a flexible and powerful probabilistic method for fusing multiple sensor observations. Sensor models exist for interpreting the range readings of sonar, laser and stereo. However, these existing sensor models do not work with radar because it provides amplitude values for many points downrange. In addition, radar has significant echo signal-to-noise variations between observations as well as limited downrange resolution. This paper presents the development of a radar sensor model, which can fuse amplitude-vector sensor data into an evidence grid. A study of radar phenomena and of frequency-modulated continuous-wave signal processing suggests rules for signal interpretation. The sensor model uses these interpretation rules and captures the volumetric beam geometry. The results include a three-dimensional map of an outdoor scene. This work is a step towards building high fidelity maps to be used in mobile robot navigation, obstacle avoidance and tool deployment under all visibility conditions.

Abstract: The paper introduces the optimal way of path planning. A dynamic grids algorithm and a dynamic obstacle avoidance algorithm have been proposed which include the position-forecasting and obstacle checking and controlling methods. An enhanced algorithm, introduced also in the paper, based on both of the technologies, results in simple and effective controlling in the soccer robot tournament.