Showing papers on "Collision avoidance published in 2004"

Nearness diagram (ND) navigation: collision avoidance in troublesome scenarios

Abstract: This paper addresses the reactive collision avoidance for vehicles that move in very dense, cluttered, and complex scenarios. First, we describe the design of a reactive navigation method that uses a "divide and conquer" strategy based on situations to simplify the difficulty of the navigation. Many techniques could be used to implement this design (since it is described at symbolic level), leading to new reactive methods that must be able to navigate in arduous environments (as the difficulty of the navigation is simplified). We also propose a geometry-based implementation of our design called the nearness diagram navigation. The advantage of this reactive method is to successfully move robots in troublesome scenarios, where other methods present a high degree of difficulty in navigating. We show experimental results on a real vehicle to validate this research, and a discussion about the advantages and limitations of this new approach.

Inevitable collision states - a step towards safer robots?

Abstract: An inevitable collision state for a robotic system can be defined as a state for which, no matter what the future trajectory followed by the system is, a collision with an obstacle eventually occurs. An inevitable collision state takes into account the dynamics of both the system and the obstacles, fixed or moving. The main contribution of this paper is to lay down and explore this novel concept (and the companion concept of inevitable collision obstacle). Formal definitions of the inevitable collision states and obstacles are given. Properties fundamental for their characterization are established. This concept is very general, and can be useful both for navigation and motion planning purposes (for its own safety, a robotic system should never find itself in an inevitable collision state). To illustrate the interest of this concept, it is applied to a problem of safe motion planning for a robotic system subject to sensing constraints in a partially known environment (i.e. that may contain unexpected obst...

Forward collision warning with a single camera

Abstract: The large number of rear end collisions due to driver inattention has been identified as a major automotive safety issue. Even a short advance warning can significantly reduce the number and severity of the collisions. This paper describes a vision based forward collision warning (FCW) system for highway safety. The algorithm described in this paper computes time to contact (TTC) and possible collision course directly from the size and position of the vehicles in the image - which are the natural measurements for a vision based system - without having to compute a 3D representation of the scene. The use of a single low cost image sensor results in an affordable system which is simple to install. The system has been implemented on real-time hardware and has been test driven on highways. Collision avoidance tests have also been performed on test tracks.

The threat of intelligent collisions

Abstract: With the advent of intelligent transportation systems (ITS), safer and more efficient roadways are on the horizon. Future generations of in-vehicle ITS will network with nearby vehicles for greater safety and efficiency. Through wireless communication and advanced sensor technologies, intelligent vehicles will learn of nearby vehicles' intentions and dynamics, and of the presence of roadway hazards. These IT technologies will allow safe, tightly spaced vehicle clusters or platoons and coordinate safe lane merges and collision avoidance in intersections and under limited-visibility conditions. For efficiency and economy, the wireless communication will probably take place directly between vehicles. The resulting intervehicle communication (IVC) network will be of the general class of mobile, ad hoc networks without a fixed infrastructure. In contrast to railroad dispatch system or air traffic control systems, which make decisions in a central location and then transmit them to trains or planes, the network will rely on ordinary nodes for routing and network management, spreading the intelligence and infrastructure throughout the network in the vehicles themselves. This article explores the IVC network's potential vulnerabilities and emerging research aimed at mitigating them. Our project, a security architecture under development called SecCar, offers a promising approach to dealing with these risks.

A Fuzzy Logic for Autonomous Navigation of Marine Vehicles Satisfying COLREG Guidelines

Abstract: An autonomous navigation algorithm for marine vehicles is proposed in this paper us- ing fuzzy logic under COLREG guidelines. The VFF (Virtual Force Field) method, which is widely used in the field of mobile robotics, is modified for application to the autonomous navi- gation of marine vehicles. This Modified Virtual Force Field (MVFF) method can be used in ei- ther track-keeping or collision avoidance modes. Moreover, the operator can select a track- keeping pattern mode in the proposed algorithm. The collision avoidance algorithm has the abil- ity to handle static and/or moving obstacles. The fuzzy expert rules are designed deliberately un- der COLREG guidelines. An extensive simulation study is used to verify the proposed method.

Collision prediction apparatus

Abstract: A collision prediction ECU of a collision prediction apparatus estimates a state of presence of a detected front obstacle. At this time, the collision prediction ECU estimates the state of presence on the basis of road shape data supplied from a navigation ECU of a navigation apparatus. Further, the collision prediction ECU checks and corrects the calculated road gradient value. At this time, the collision prediction ECU corrects the gradient value on the basis of road gradient data supplied from the navigation ECU. Further, the collision prediction ECU changes a collision avoidance time on the basis of travel environment data supplied from the navigation ECU. Moreover, the collision prediction ECU obtains an ETC gate pass-through signal from the navigation ECU and determines whether the vehicle is passing through the gate. The collision prediction apparatus performs collation prediction on the basis of the corrected values.

Decentralized cooperative search by networked UAVs in an uncertain environment

Abstract: This paper addresses the problem of cooperative search in a given environment by a team of unmanned aerial vehicles (UAVs). We present a decentralized control model for cooperative search and develop a real-time approach for online cooperation among vehicles, which is based on treating the possible paths of other vehicles as "soft obstacles" to be avoided. Using the approach of "rivaling force" between vehicles to enhance cooperation, each UAV takes into account the possible actions of other UAVs such that the overall information about the environment is increased. The simulation results illustrate the effectiveness of the proposed strategy.

A "divide and conquer" strategy based on situations to achieve reactive collision avoidance in troublesome scenarios

Abstract: This paper addresses reactive collision avoidance for robots that move in arduous environments (i.e., very dense, complex and cluttered). To achieve this goal, the technique simplifies the difficulty of the navigation by a divide and conquer strategy, which is based on identifying navigational situations and applying the corresponding motion laws. The state of the art in reactive navigation still presents classic limitations such as trap situations due to U-shape obstacles, difficulty to achieve motion among very close obstacles, to obtain oscillation-free and stable motion, to move over directions far from the goal direction or towards the obstacles, or to tune the heuristic or internal parameters. This paper presents a method that overcomes all these limitations. As a result, navigation with this method is successfully achieved in scenarios where existing techniques present a high degree of difficulty to navigate. Outstanding navigation results are reported using a wheelchair vehicle. A discussion and comparison with existing techniques is provided.

COLREGS-based navigation of autonomous marine vehicles

Abstract: This paper addresses the issue of autonomous control and safe navigation in an unmanned marine vehicle. Primarily it is concerned with the issue of effective collision avoidance. The first part of the paper examines known legal issues regarding autonomous marine vehicles, and the second part addresses how to provide an autonomous COLREGS capability in an autonomous marine vehicle.

An IMM Algorithm for Tracking Maneuvering Vehicles in an Adaptive Cruise Control Environment

Abstract: In this paper, an unscented Kalman filter (UKF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, an UKF is used because of the drawbacks of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions. 1. INTRODUCTON Recently, the majority of automobile companies are developing various driver assistance systems to increase vehicle safety and alleviate driver workload. The driver assistance systems include adaptive cruise control (ACC), lane-keeping support, collision warning and collision avoidance, and assisted lane changes. The effectiveness of these driver assistant systems depends on the interpretation of the information arriving from sensors, which provide details of the surrounding vehicle environment and of the driver-assisted vehicle itself. In particular, all these systems rely on the detection and subsequent tracking of objects around the vehicle. Such detection information is provided by radar, lidar, and vision sensor. The assistance systems mentioned above have certain objectives that their controllers try to meet. Before a controller can make a decision that enables the driver to feel natural, the motion of the surrounding object must be properly interpreted from the available sensor information (2).

The DARPA grand challenge - development of an autonomous vehicle

Abstract: The DARPA Grand Challenge (DGC) was an opportunity to test autonomous vehicles in a competitive situation. In addition to intelligent behaviour, the participating vehicles must also exhibit ruggedness and endurance in order to survive the fast ride over rough terrain ("win with the software- lose with the hardware"). The SciAutonics teams decided to use compact and agile vehicles that employ proven mechanical designs very suitable for the desert environment. 4-wheel drive ensures robust controllability even in slippery ground, and a roll cage protects the vehicle components from damage in case of a collision. The control system relies primarily on a differential GPS (Starfire) and a set of inertial sensors for navigating between the given set of waypoints. A sensor suite using infrared laser (LIDAR) and ultrasound sensing provides the capability of obstacle avoidance and path following. This paper shows the components of the vehicle and results from driving at the DGC.

Proportional Navigation-Based Optimal Collision Avoidance for UAVs

Abstract: This research was performed for the Smart UAV Development Program, one of 21st Centry Frontier R&D Program funded by the Ministry of Science and Technology of Korea.

Design and experimental study of an ultrasonic sensor system for lateral collision avoidance at low speeds

Abstract: In this study, we-design and implement an ultrasonic sensor system for lateral collision avoidance of vehicles at low speeds The developed sensor system is useful for detecting vehicles, motorcycles, bicycles and pedestrians that pass by the lateral side of a vehicle The system can be adopted to enhance the rear-view mirrors of present vehicles, which have blind spots on the lateral sides Ultrasonic sensors, which have been widely used on cars for rear object detection during parking, are developed for lateral object detection at low speeds Detailed experimental studies are presented in this paper Experimental results show that the proposed system can detect a vehicle at speeds up to 40 km/hr with a maximum range of 6 meters Moreover, the influence of wind on the measurement is also investigated The developed sensor system gives satisfactory results for a wind speed up to 35 km/hr

Stereo-vision based imminent collision detection

Abstract: A stereo vision based collision avoidance systems having stereo cameras that produce imagery that is processed to produce a depth map of a scene. A potential threat is detected in the depth map. The size, position, and velocity of the detected potential threat are then estimated, and a trajectory analysis of the detected potential threat is determined using the estimated position and the estimated velocity. A collision prediction based on the trajectory analysis is determined, and then a determination is made as to whether a collision is imminent based on the collision prediction and on the estimated size of the potential threat.

Collision avoidance involving radar feedback

Abstract: Collision avoidance systems and methods are implemented on unmanned mobile vehicles to supplement map-based trajectories generated by the vehicles' navigation systems. These systems include radar, which detect obstacles in the path of the unmanned mobile vehicles, and collision avoidance modules, which enable the vehicles to avoid unexpected obstacles by adjusting their trajectories and velocities based on feedback received from the radar. In general, when an obstacle is detected by the radar, the collision avoidance module modifies the commanded velocity of an unmanned mobile vehicle by subtracting from the nominal commanded velocity the component that is in the direction of the obstacle. The magnitude of the velocity modification typically increases as the distance between the mobile vehicle and the obstacle decreases.

VPH: a new laser radar based obstacle avoidance method for intelligent mobile robots

Abstract: Real-time obstacle avoidance is one of the key issues in successful application of mobile robot systems. Some new real-time obstacle avoidance methods for mobile robots have already been developed and implemented. This paper introduces the developments in this area, and summarizes Potential Field method (PFM) and the Enhanced Vector Field Histogram method (VFH+), which are widely used for autonomous mobile robot obstacle avoidance. After a brief introduction of laser measurement system (LMS), a new radar-based obstacle avoidance method for mobile robots, based on the combination and improvement of PFM and VFH+ method, is presented. This method, named the Vector Polar Histogram method (VPH), uses laser radar to detect obstacles and takes the physical meaning of the vector polar into account, so as to get the best avoidance choice. The new method permits the detection of unknown obstacles and avoids collisions in real time while simultaneously steering the mobile robot towards the target.

Parking maneuvers of industrial-like electrical vehicles with and without trailer

Abstract: Maneuvering autonomous vehicles in constrained environments is not a trivial task. This paper concentrates in the practical maneuvering of electrical vehicles. The autonomous vehicles considered in the paper, ROMEO-3R and ROMEO-4R, have been developed at the University of Seville, Seville, Spain, as the result of the adaptation of a tricycle and a car-like conventional electrical vehicles for transportation of people, respectively. Moreover, maneuvering of ROMEO-4R backing up a trailer has also been considered. A particular maneuver, namely, autonomous parallel parking, has been used to illustrate the application of the presented methods to different electrical vehicles.

Embedded free flight obstacle avoidance system

Abstract: A free flight obstacle avoidance system (OAS) (60) is a commanded obstacle resolution feedback system. The system employs insertion of hybridized elements to the existing designs of Adaptive Ground Collision Avoidance Systems and Midair Collision Avoidance Systems along with a newly design module, the obstacle avoidance dispatcher and resolver (65), to provide a coherent obstacle resolution. The system is capable of filtering data produced by the hybrid ground collision avoidance module (66) and the hybrid air collision avoidance module (67), inserting evaluating solution status and command directives before routing avoidance data to hybrid modules for validation. The dispatcher and resolver module (65) determines the final obstacle resolution (203) to generate avoidance control guidance (216) and appropriate warnings (217) clearly indicated obstacle situation and obstacle avoidance maneuvers (218) to the flight crew. In addition to the avoidance capabilities, the system also provides extended functions of terrain following guidance (308) and space separation warnings (210).

Obstacle avoidance with sensor uncertainty for small unmanned aircraft

Abstract: The ability to detect, sense, and avoid obstacles in the environment is a critical capability for autonomous groups of unmanned aircraft. The overall obstacle avoidance problem is typically studied as two or three separate subproblems. Unfortunately, such an approach can lead to unrealistic assumptions being made about the other subsystems or specification of unnecessarily high levels of subsystem performance. In this paper, we present an approach to obstacle avoidance in the context of a multilayered, multi-objective control architecture that considers both the aircraft dynamics and sensor limitations in an integrated framework. Specifically, the concept of reachable sets is extended to include the error model of parallel-baseline, stereovision. An analytical solution is presented for the planar motion of a single unmanned aircraft. In addition, the extension to groups of UAV is introduced.

Experimental study of curvature-based control laws for obstacle avoidance

Abstract: A novel curvature-based steering control law is introduced to produce obstacle avoidance behavior for unicycle type robots traveling (flying) at constant speed. Different methods of curvature estimation from noisy range data are explored and compared via experiments. The performance of the obstacle avoidance algorithm is investigated through simulations and experiments.

Collision avoidance control system for vehicle

Abstract: A collision avoidance control system for a vehicle is provided which is designed to determine a target collision avoidance deceleration required for a system vehicle equipped with this system to bring a relative speed between the system vehicle and a target object into agreement with substantially zero without a physical collision with the target object and to determine a possibility of collision with the target object as a function of the target collision avoidance deceleration. When the possibility of collision is higher than a given threshold level, the system starts to decelerate the system vehicle. This enables the avoidance of collision with the target object at a decreased operation load on the system.

Vehicle rear-end collision prevention or severity reduction method, transmitting warning to following vehicle if collision appears likely and or avoiding actions are automatically triggered in lead vehicle

Abstract: Method for reducing the risk of a read-end collision in which if a collision is identified as likely, a warning (W, W1, W2) is transmitted from the first vehicle (1) to the following second vehicle (2) and or avoiding actions are triggered in the first vehicle. The warning may be optical, e.g. by blinking or changing the brightness of brake lights, acoustic, or haptic, or a combination of these. An independent claim is included for a device for implementing the collision avoidance method of the invention.

Modeling of collision avoidance protocols in single-channel multihop wireless networks

Abstract: Although there has been considerable work on the performance evaluation of collision avoidance schemes, most analytical work is confined to single-hop ad hoc networks or networks with very few hidden terminals. We present the first analytical model to derive the saturation throughput of collision avoidance protocols in multi-hop ad hoc networks with nodes randomly placed according to a two-dimensional Poisson distribution. We show that the sender-initiated collision-avoidance scheme achieves much higher throughput than the ideal carrier sense multiple access scheme with a separate channel for acknowledgments. More importantly, we show that the collision-avoidance scheme can accommodate much fewer competing nodes within a region in a network infested with hidden terminals than in a fully-connected network, if reasonable throughput is to be maintained. Simulations of the IEEE 802.11 MAC protocol and one of its variants validate the predictions made in the analysis. It is also shown that the IEEE 802.11 MAC protocol cannot ensure collision-free transmission of data packets and thus throughput can degrade well below what is predicted by the analysis of a correct collision avoidance protocol. Based on these results, a number of improvements are proposed for the IEEE 802.11 MAC protocol.

A collision avoidance model based on the Lobula giant movement detector (LGMD) neuron of the locust

Abstract: In insects, we can find very complex and compact neural structures that are task specific. These neural structures allow them to perform complex tasks such as visual navigation, including obstacle avoidance, landing, self-stabilization, etc. Obstacle avoidance is fundamental for successful navigation, and it can be combined with more systems to make up more complex behaviors. In this paper, we present a model for collision avoidance based on the Lobula giant movement detector (LGMD) cell of the locust. This is a wide-field visual neuron that responds to looming stimuli and that can trigger avoidance reactions whenever a rapidly approaching object is detected. Here, we present result based on both an offline study of the model and its application to a flying robot.

Combined road prediction and target tracking in collision avoidance

Abstract: Detection and tracking of other vehicles and lane geometry will be required for many future intelligent driver assistance systems. By integrating the estimation of these two features into a single filter, a more optimal utilization of the available information can be achieved. For example, it is possible to improve the lane curvature estimate during bad visibility by studying the motion of other vehicles. This paper derives and evaluates various approximations that are needed in order to deal with the non-linearities that are introduced by such an approach.

Nonlinear mixed integer programming for aircraft collision avoidance in free flight

Abstract: This paper addresses the problem of conflict avoidance in Air Traffic Management (ATM) systems. Aircraft are assumed to travel in a shared airspace and collaborate for solving the conflicts by sharing information. Aircraft can not get closer to each other than a given safety distance and each aircraft's goal is to reach its final destination in minimum time, while avoiding all potential conflicts. We propose a combination of the velocity control (VC) and heading angle control (HAC) methods that produces a more realistic but also more complex method. The new problem is a mixed-integer programming one and we solve it using standard optimization software.

Collision avoidance for a remotely-operated helicopter using haptic feedback

Abstract: This paper introduces four new collision avoidance systems for a remotely-operated helicopter using haptic feedback on the control stick of the operator. To calculate the feedback force artificial risk fields are used, which give an indication about the risk of hitting an obstacle. For each obstacle in the risk field a risk value is calculated, which is transformed to a risk vector, acting as an artificial force on the vehicle. All risk vectors are integrated into one avoidance vector, which is proportional to the feedback force to the operator. A basic risk field and a parameterized risk field are tested in simulations, together with two risk vector calculation methods, resulting in radial and normal risk vectors. The simulations show most promising results for the parameterized risk field with radial risk vectors and worst results for the basic risk field with normal vectors

Obstacle awareness and collision avoidance radar sensor system for low-altitude flying smart UAV

Abstract: In This work, the critical requirement for obstacle awareness and avoidance is assessed with the compliance of the equivalent level of safety regulation, and then the collision avoidance sensor system is presented with the key design parameters for the requirement of the smart unmanned aerial vehicle in low-altitude flight. Based on the assessment of various sensors, small-sized radar sensor is selected for the suitable candidate due to the real-time range and range-rate acquisition capability of the stationary and moving aircraft even under all-weather environments. Through the performance analysis for the system requirement, the conceptual design result of radar sensor model is proposed with the range detection probability and collision avoidance performance in a typical flight environment.