Showing papers on "Collision avoidance published in 2012"

FCL: A general purpose library for collision and proximity queries

Abstract: We present a new collision and proximity library that integrates several techniques for fast and accurate collision checking and proximity computation. Our library is based on hierarchical representations and designed to perform multiple proximity queries on different model representations. The set of queries includes discrete collision detection, continuous collision detection, separation distance computation and penetration depth estimation. The input models may correspond to triangulated rigid or deformable models and articulated models. Moreover, FCL can perform probabilistic collision checking between noisy point clouds that are captured using cameras or LIDAR sensors. The main benefit of FCL lies in the fact that it provides a unified interface that can be used by various applications. Furthermore, its flexible architecture makes it easier to implement new algorithms within this framework. The runtime performance of the library is comparable to state of the art collision and proximity algorithms. We demonstrate its performance on synthetic datasets as well as motion planning and grasping computations performed using a two-armed mobile manipulation robot.

A depth space approach to human-robot collision avoidance

Abstract: In this paper a real-time collision avoidance approach is presented for safe human-robot coexistence. The main contribution is a fast method to evaluate distances between the robot and possibly moving obstacles (including humans), based on the concept of depth space. The distances are used to generate repulsive vectors that are used to control the robot while executing a generic motion task. The repulsive vectors can also take advantage of an estimation of the obstacle velocity. In order to preserve the execution of a Cartesian task with a redundant manipulator, a simple collision avoidance algorithm has been implemented where different reaction behaviors are set up for the end-effector and for other control points along the robot structure. The complete collision avoidance framework, from perception of the environment to joint-level robot control, is presented for a 7-dof KUKA Light-Weight-Robot IV using the Microsoft Kinect sensor. Experimental results are reported for dynamic environments with obstacles and a human.

Autonomous Ground Vehicles—Concepts and a Path to the Future

Abstract: Autonomous vehicles promise numerous improvements to vehicular traffic: an increase in both highway capacity and traffic flow because of faster response times, less fuel consumption and pollution thanks to more foresighted driving, and hopefully fewer accidents thanks to collision avoidance systems. In addition, drivers can save time for more useful activities. In order for these vehicles to safely operate in everyday traffic or in harsh off-road environments, a multitude of problems in perception, navigation, and control have to be solved. This paper gives an overview of the most current trends in autonomous vehicles, highlighting the concepts common to most successful systems as well as their differences. It concludes with an outlook into the promising future of autonomous vehicles.

Safety Benefits of Forward Collision Warning, Brake Assist, and Autonomous Braking Systems in Rear-End Collisions

Abstract: This paper examines the potential effectiveness of the following three precollision system (PCS) algorithms: 1) forward collision warning only; 2) forward collision warning and precrash brake assist; and 3) forward collision warning, precrash brake assist, and autonomous precrash brake. Real-world rear-end crashes were extracted from a nationally representative sample of collisions in the United States. A sample of 1396 collisions, corresponding to 1.1 million crashes, were computationally simulated as if they occurred, with the driver operating a precollision-system-equipped vehicle. A probability-based framework was developed to account for the variable driver reaction to the warning system. As more components were added to the algorithms, greater benefits were realized. The results indicate that the exemplar PCS investigated in this paper could reduce the severity (i.e., ΔV) of the collision between 14% and 34%. The number of moderately to fatally injured drivers who wore their seat belts could have been reduced by 29% to 50%. These collision-mitigating algorithms could have prevented 3.2% to 7.7% of rear-end collisions. This paper shows the dramatic reductions in serious and fatal injuries that a PCS, which is one of the first intelligent vehicle technologies to be deployed in production cars, can bring to highway safety when available throughout the fleet. This paper also presents the framework of an innovative safety benefits methodology that, when adapted to other emerging active safety technologies, can be employed to estimate potential reductions in the frequency and severity of highway crashes.

Integrated control for pHRI: Collision avoidance, detection, reaction and collaboration

Abstract: We present an integrated control framework for safe physical Human-Robot Interaction (pHRI) based on a hierarchy of consistent behaviors. Safe human robot coexistence is achieved with a layered approach for coping with undesired collisions and intended contacts. A collision avoidance algorithm based on depth information of the HRI scene is used in the first place. Since collision avoidance cannot be guaranteed, it is supported by a physical collision detection/reaction method based on a residual signal which needs only joint position measures. On top of this layer, safe human-robot collaboration tasks can be realized. Collaboration phases are activated and ended by human gestures or voice commands. Intentional physical interaction is enabled and exchanged forces are estimated by integrating the residual with an estimation of the contact point obtained from depth sensing. During the collaboration, only the human parts that are designated as collaborative are allowed to touch the robot while, consistently to the lower layers, all other contacts are considered undesired collisions. Preliminary experimental results with a KUKA LWR-IV and a Kinect sensor are presented.

An Intelligent V2I-Based Traffic Management System

Abstract: Vehicles equipped with intelligent systems designed to prevent accidents, such as collision warning systems (CWSs) or lane-keeping assistance (LKA), are now on the market. The next step in reducing road accidents is to coordinate such vehicles in advance not only to avoid collisions but to improve traffic flow as well. To this end, vehicle-to-infrastructure (V2I) communications are essential to properly manage traffic situations. This paper describes the AUTOPIA approach toward an intelligent traffic management system based on V2I communications. A fuzzy-based control algorithm that takes into account each vehicle's safe and comfortable distance and speed adjustment for collision avoidance and better traffic flow has been developed. The proposed solution was validated by an IEEE-802.11p-based communications study. The entire system showed good performance in testing in real-world scenarios, first by computer simulation and then with real vehicles.

COLREGs-based collision avoidance strategies for unmanned surface vehicles

Abstract: The aim of this paper is to report the preliminary development of an automatic collision avoidance technique for unmanned marine craft based on standardised rules, COLREGs, defined by the International Maritime Organisation. It is noted that all marine surface vessels are required to adhere to COLREGs at all times in order to minimise or eliminate the risk of collisions. The approach presented is essentially a reactive path planning algorithm which provides feedback to the autopilot of an unmanned vessel or the human captain of a manned ship for steering the craft safely. The proposed strategy consists of waypoint guidance by line-of-sight coupled with a manual biasing scheme. This is applied to the dynamic model of an unmanned surface vehicle. A simple PID autopilot is incorporated to ensure that the vessel adheres to the generated seaway. It is shown through simulations that the resulting scheme is able to generate viable trajectories in the presence of both stationary and dynamic obstacles. Rules 8 and 14 of the COLREGs, which apply to the amount of manoeuvre and to a head-on scenario respectively are simulated. A comparison is also made with an offline or deliberative grid-based path planning algorithm which has been modified to generate COLREGs-compliant routes.

Next-Generation Airborne Collision Avoidance System

Abstract: : In response to a series of midair collisions involving commercial airliners, Lincoln Laboratory was directed by the Federal Aviation Administration in the 1970s to participate in the development of an onboard collision avoidance system. In its current manifestation, the Traffic Alert and Collision Avoidance System is mandated worldwide on all large aircraft and has significantly improved the safety of air travel, but major changes to the airspace planned over the coming years will require substantial modification to the system. Recently, Lincoln Laboratory has been pioneering the development of a new approach to collision avoidance systems that completely rethink show such systems are engineered, allowing the system to provide a higher degree of safety without interfering with normal, safe operations.

Intersection management for autonomous vehicles using iCACC

Abstract: Recently several artificial intelligence labs have suggested the use of fully equipped vehicles with the capability of sensing the surrounding environment to enhance roadway safety. As a result, it is anticipated in the future that many vehicles will be autonomous and thus there is a need to optimize the movement of these vehicles. This paper presents a new tool for optimizing the movements of autonomous vehicles through intersections: iCACC. The main concept of the proposed tool is to control vehicle trajectories using Cooperative Adaptive Cruise Control (CACC) systems to avoid collisions and minimize intersection delay. Simulations were executed to compare conventional signal control with iCACC considering two measures of effectiveness - delay and fuel consumption. Savings in delay and fuel consumption in the range of 91 and 82 percent relative to conventional signal control were demonstrated, respectively.

Reciprocal collision avoidance for multiple car-like robots

Abstract: In this paper a method for distributed reciprocal collision avoidance among multiple non-holonomic robots with bike kinematics is presented. The proposed algorithm, bicycle reciprocal collision avoidance (B-ORCA), builds on the concept of optimal reciprocal collision avoidance (ORCA) for holonomic robots but furthermore guarantees collision-free motions under the kinematic constraints of car-like vehicles. The underlying principle of the B-ORCA algorithm applies more generally to other kinematic models, as it combines velocity obstacles with generic tracking control. The theoretical results on collision avoidance are validated by several simulation experiments between multiple car-like robots.

UAV Formation Flight Based on Nonlinear Model Predictive Control

Abstract: We designed a distributed collision-free formation flight control law in the framework of nonlinear model predictive control. Formation configuration is determined in the virtual reference point coordinate system. Obstacle avoidance is guaranteed by cost penalty, and intervehicle collision avoidance is guaranteed by cost penalty combined with a new priority strategy.

Systems and methods for insurance based upon monitored characteristics of a collision detection system

Abstract: A property of an insurance policy may be determined, at least in part, upon characteristics of a vehicle collision detection system. The characteristics may pertain to any capability, configuration, and/or operating state of the collision detection system (and/or vehicle). For example, a property of the insurance policy may be based upon whether the collision detection system is configured to take automatic collision avoidance actions in response to detecting a potential collision and/or whether the automatic collision avoidance actions can be overridden by the operator of the vehicle. The property of the insurance policy may be dynamic, and may be updated in response to changes to the collision detection system and/or the real-time operating state thereof. The coverage of particular events may be based upon characteristics of the collision detection system and/or vehicle at the time the event occurred.

Intelligent Ocean Navigation and Fuzzy-Bayesian Decision/Action Formulation

Abstract: This paper focuses on the formulation of a decision-action execution model that can facilitate intelligent collision avoidance features in ocean navigation systems, while respecting the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) rules and regulations of collision avoidance. The decision/action process in this work consists of a fuzzy-logic-based parallel decision-making (PDM) module whose decisions are formulated into sequential actions by a Bayesian-network-based module. Therefore, the paper presents a collision avoidance system (CAS) that is capable of making multiple parallel collision avoidance decisions regarding several target vessel collision conditions, and those decisions are executed as sequential actions to avoid complex collision situations in ocean navigation.

Multi-robot collision avoidance with localization uncertainty

Abstract: This paper describes a multi-robot collision avoidance system based on the velocity obstacle paradigm. In contrast to previous approaches, we alleviate the strong requirement for perfect sensing (i.e. global positioning) using Adaptive Monte-Carlo Localization on a per-agent level. While such methods as Optimal Reciprocal Collision Avoidance guarantee local collision-free motion for a large number of robots, given perfect knowledge of positions and speeds, a realistic implementation requires further extensions to deal with inaccurate localization and message passing delays. The presented algorithm bounds the error introduced by localization and combines the computation for collision-free motion with localization uncertainty. We provide an open source implementation using the Robot Operating System (ROS). The system is tested and evaluated with up to eight robots in simulation and on four differential drive robots in a real-world situation.

Steering Assist in Driver Initiated Collision Avoidance Maneuver

Abstract: A collision avoidance system for assisting a driver in avoiding a collision between a host vehicle and obstacle. A processor recursively calculates a time-to-collision with the obstacle and an optimal collision avoidance path for avoiding the collision. The optimum collision avoidance path is recursively generated based on a position and speed of the host vehicle relative to the obstacle and an updated calculated time-to-collision. A sensing device determines whether the driver of the vehicle has initiated a steering maneuver to avoid the obstacle. A steering assist mechanism maintains the host vehicle along the optimum collision avoidance path. The steering assist mechanism applies a steering assist torque for producing steering adjustments to assist in guiding the host vehicle along the optimum collision avoidance path to the target lane. The steering assist torque generated by the steering assist mechanism is recursively adjusted based on a recent updated optimum collision avoidance path.

A Review of Near-Collision Driver Behavior Models

Abstract: Objective:This article provides a review of recent models of driver behavior in on-road collision situations.Background:In efforts to improve traffic safety, computer simulation of accident situations holds promise as a valuable tool, for both academia and industry. However, to ensure the validity of simulations, models are needed that accurately capture near-crash driver behavior, as observed in real traffic or driving experiments.Method:Scientific articles were identified by a systematic approach, including extensive database searches. Criteria for inclusion were defined and applied, including the requirement that models should have been previously applied to simulate on-road collision avoidance behavior. Several selected models were implemented and tested in selected scenarios.Results:The reviewed articles were grouped according to a rough taxonomy based on main emphasis, namely avoidance by braking, avoidance by steering, avoidance by a combination of braking and steering, effects of driver states and...

LQG-obstacles: Feedback control with collision avoidance for mobile robots with motion and sensing uncertainty

Abstract: This paper presents LQG-Obstacles, a new concept that combines linear-quadratic feedback control of mobile robots with guaranteed avoidance of collisions with obstacles. Our approach generalizes the concept of Velocity Obstacles [3] to any robotic system with a linear Gaussian dynamics model. We integrate a Kalman filter for state estimation and an LQR feedback controller into a closed-loop dynamics model of which a higher-level control objective is the “control input”. We then define the LQG-Obstacle as the set of control objectives that result in a collision with high probability. Selecting a control objective outside the LQG-Obstacle then produces collision-free motion. We demonstrate the potential of LQG-Obstacles by safely and smoothly navigating a simulated quadrotor helicopter with complex non-linear dynamics and motion and sensing uncertainty through three-dimensional environments with obstacles and narrow passages.

Pedestrian-inspired sampling-based multi-robot collision avoidance

Abstract: We present a distributed collision avoidance algorithm for multiple mobile robots that is model-predictive, sampling-based, and intuitive for operation around humans. Unlike purely reactive approaches, the proposed algorithm incorporates arbitrary trajectories as generated by a motion planner running on each navigating robot as well as predicted human trajectories. Our approach, inspired by human navigation in crowded pedestrian environments, draws from the sociology literature on pedestrian interaction. We propose a simple two-phase algorithm in which agents initially cooperate to avoid each other and then initiate civil inattention, thus lessening reactivity and committing to a trajectory. This process entails a pedestrian bargain in which all agents act competently to avoid each other and, once resolution is achieved, to avoid interfering with others' planned trajectories. This approach, being human-inspired, fluidly permits navigational interaction between humans and robots. We report experimental results for the algorithm running on real robots with and without human presence and in simulation.

Automatic collision avoidance using model-predictive online optimization

Abstract: In many traffic emergency situations a collision cannot be prevented by braking alone. Therefore, we propose an obstacle avoidance algorithm that simultaneously optimizes steering and braking. As an emergency scenario approaches the driving limits, a strong nonlinear constraint between braking and cornering develops, suggesting the formulation of a nonlinear constrained online optimization. On this account the proposed algorithm embarks on the nonlinear model-predictive control (NMPC) paradigm, which is capable of solving the optimization problem online. The performance of the algorithm is demonstrated in a simulated pedestrian collision avoidance scenario.

Fluent coordination of autonomous vehicles at intersections

Abstract: In this paper we introduce a new decentralized navigation function for coordination of autonomous vehicles at intersections. The main contribution is a navigation function designed for vehicles with predefined paths that uses expected time to intersection for collision avoidance. In such way, deadlock situations are avoided. Different inertias of the vehicles are taken into account to enable on-board energy optimization for crossing. Heavier vehicles that need more energy and time for acceleration or braking are given an indirect priority at intersections. The proposed decentralized coordination scheme shows a significant improvement in energy consumption and in motion smoothness compared to traditional crossing with human drivers.

Collision avoidance under bounded localization uncertainty

Abstract: We present a multi-mobile robot collision avoidance system based on the velocity obstacle paradigm. Current positions and velocities of surrounding robots are translated to an efficient geometric representation to determine safe motions. Each robot uses on-board localization and local communication to build the velocity obstacle representation of its surroundings. Our close and error-bounded convex approximation of the localization density distribution results in collision-free paths under uncertainty. While in many algorithms the robots are approximated by circumscribed radii, we use the convex hull to minimize the overestimation in the footprint. Results show that our approach allows for safe navigation even in densely packed environments.

Multiagent Approach for Real-Time Collision Avoidance and Path Replanning for Cranes

Abstract: Collisions on construction sites are one of the primary causes of fatal accidents. This paper proposes a multiagent-based approach to provide real-time support to the staff of construction projects. Collision avoidance is achieved by informing the crane operators about potential collisions and by providing motion replanning for crane operations. During the planning stage, a three-dimensional (3D) model of the static environment is created, and collision-free motion plans are generated by the agents for the cranes, considering engineering constraints and operation rules. During actual construction work, all mobile objects are tagged when entering the monitored area. A site state agent uses a real-time location system (RTLS), such as an ultra-wideband (UWB) system to collect location data, calculates the poses of the objects on site, and sends this information to other agents. By using this real-time updated information, agents can detect potential collisions and replan the path for the cranes for c...

Path planning and collision avoidance for robots

Abstract: An optimal control problem to find the fastest collision-free trajectory of a robot surrounded by obstacles is presented. The collision avoidance is based on linear programming arguments and expressed as state constraints. The optimal control problem is solved with a sequential programming method. In order to decrease the number of unknowns and constraints a backface culling active set strategy is added to the resolution technique.

Vehicle-to-Vehicle IEEE 802.11p performance measurements at urban intersections

Abstract: During the last few years, vehicle-to-vehicle (V2V) wireless communication has become a key objective for enabling future cooperative safety applications, such as intersection collision warning. In this paper, we present the results of a 5.9 GHz V2V performance measurement campaign at four different urban intersections under NLOS conditions using commercial off-the-shelf wireless interface cards which meet the 802.11p and ITS-G5 specifications. Particularly, we quantify the packet delivery ratio (PDR) and received signal strength indication (RSSI) levels associated with different scenario conditions with respect to vehicle positioning, intersection geometry and traffic density. We determine reliable communication ranges which constitute an important metric for V2V collision avoidance applications.

Fuzzy Decision on Optimal Collision Avoidance Measures for Ships in Vessel Traffic Service

Abstract: This article proposes a new collision avoidance decision method for ships, allowing ships at risk of collision to take timely collision avoidance measures to ensure safe passage. Through vessel traffic service (VTS) collision alert system, an analysis can be made for the probability of a ship collision and an early warning can be issued. For ships in potential collision danger, the proposed method will use Microsoft Visual Studio to establish a knowledge base of international regulations for preventing collisions at sea. Thus, based on an analysis of the situation when encountering other ships, the knowledge base will suggest an appropriate avoidance technique and use a fuzzy monitoring system, propose a novel collision danger domain that forbids entering forgive-way ship. Considering the required advance for ship turning, the fuzzy monitoring system will suggest the optimal rudder steering procedure for the give-way ship, allow the ship to avoid collision and ensure navigation safety. The avoidance action taken by the ship does not consider reducing speed, instead focuses only on rudder steering. The system also integrates VTS/automatic identification system (AIS)/marine geographic information system (MGIS) by using MGIS as an AIS imaging system to facilitate the optimal decision for ship collision avoidance and determine the input linguistic variables for the fuzzy logic theory via an analytical hierarchy process. The proposed method can enhance the VTS operator's decision-making abilities for collision avoidance by providing a fuzzy monitoring system.

Cooperative driving and collision avoidance by distributed receding horizon control

Abstract: Distributed control of vehicles with coordinating cars that implement a cooperative control method, and non-coordinating cars that are presumed to follow predictable dynamics. A cooperative control method can combine distributed receding horizon control, for optimization-based path planning and feedback, with higher level logic, to ensure that implemented plans are collision free. The cooperative method can be completely distributed with partially synchronous execution, and can afford dedicated time for communication and computation, features that are prerequisites for implementation on real freeways. The method can test for conflicts and can calculate optimized trajectories by adjusting parameters in terminal state constraints of an optimal control problem.

A Stochastic Model for Chain Collisions of Vehicles Equipped With Vehicular Communications

Abstract: Improvement of traffic safety by cooperative vehicular applications is one of the most promising benefits of vehicular ad hoc networks (VANETs) However, to properly develop such applications, the influence of different driving parameters on the event of vehicle collision must be assessed at an early design stage In this paper, we derive a stochastic model for the number of accidents in a platoon of vehicles equipped with a warning collision notification system, which is able to inform all the vehicles about an emergency event In fact, the assumption of communications being used is key to simplify the derivation of a stochastic model The model enables the computation of the average number of collisions that occur in the platoon, the probabilities of the different ways in which the collisions may take place, as well as other statistics of interest Although an exponential distribution has been used for the traffic density, it is also valid for different probability distributions for traffic densities, as well as for other significant parameters of the model Moreover, the actual communication system employed is independent of the model since it is abstracted by a message delay variable, which allows it to be used to evaluate different communication technologies We validate the proposed model with Monte Carlo simulations With this model, one can quickly evaluate numerically the influence of different model parameters (vehicle density, velocities, decelerations, and delays) on the collision process and draw conclusions that shed relevant guidelines for the design of vehicular communication systems, as well as chain collision avoidance applications Illustrative examples of application are provided, although a systematic characterization and evaluation of different scenarios is left as future work