This paper presents a method for robot motion planning in dynamic environments. It consists of selecting avoidance maneuvers to avoid static and moving obstacles in the velocity space, based on the cur rent positions and velocities of the robot and obstacles. It is a first- order method, since it does not integrate velocities to yield positions as functions of time.The avoidance maneuvers are generated by selecting robot ve locities outside of the velocity obstacles, which represent the set of robot velocities that would result in a collision with a given obstacle that moves at a given velocity, at some future time. To ensure that the avoidance maneuver is dynamically feasible, the set of avoidance velocities is intersected with the set of admissible velocities, defined by the robot's acceleration constraints. Computing new avoidance maneuvers at regular time intervals accounts for general obstacle trajectories.The trajectory from start to goal is computed by searching a tree of feasible avoidance maneuve...

Motion Planning in Dynamic Environments Using Velocity Obstacles

Surveys the developments of the last 20 years in the area of vision for mobile robot navigation. Two major components of the paper deal with indoor navigation and outdoor navigation. For each component, we have further subdivided our treatment of the subject on the basis of structured and unstructured environments. For indoor robots in structured environments, we have dealt separately with the cases of geometrical and topological models of space. For unstructured environments, we have discussed the cases of navigation using optical flows, using methods from the appearance-based paradigm, and by recognition of specific objects in the environment.

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Vision for mobile robot navigation: a survey

This paper presents heuristic methods for motion planning in dynamic environments, based on the concept of Velocity Obstacle (VO).

Heuristic Motion Planning in Dynamic Environments Using Velocity Obstacles

Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of state-of-the-art is improved further. This paper discusses unsolved problems and surveys the technical aspect of automated driving. Studies regarding present challenges, high-level system architectures, emerging methodologies and core functions including localization, mapping, perception, planning, and human machine interfaces, were thoroughly reviewed. Furthermore, many state-of-the-art algorithms were implemented and compared on our own platform in a real-world driving setting. The paper concludes with an overview of available datasets and tools for ADS development.

A Survey of Autonomous Driving: Common Practices and Emerging Technologies

Scan registration is an essential sub-task when building maps based on range finder data from mobile robots. The problem is to deduce how the robot has moved between consecutive scans, based on the ...

/pdf/scan-registration-for-autonomous-mining-vehicles-using-3d-vjm5066ql4.pdf

Scan registration for autonomous mining vehicles using 3D-NDT

A 3D scan matching is an important component for sensor based localization and mapping by a mobile robot in natural environment. In this paper, the present authors propose a way to extend 2D normal distributions transform (NDT) scan matching method to 3D scan matching, and its improvement for faster processing time. This scan matching method divides scan into voxels, and approximates scan points in each cell into normal distribution. That matching time is O(N) with N of the number of input scan points. The authors describe in this paper, NDT for 3D scan points, its acceleration using the dual resolutions of NDT, and experiments of map building in large scale environments

A 3-D Scan Matching using Improved 3-D Normal Distributions Transform for Mobile Robotic Mapping

The authors aim at map based outdoor navigation of a mobile robot. In navigation, robot position is fundamentally obtained by odometry. However, the position is misaligned as the robot moves because odometry has cumulative error. DGPS measurement data may cancel its position error. The framework of EKF is used for the modification and the fusion between odometry and DGPS measurement data. The DGPS measurement data, however, could have large error because of multipath near buildings. In this paper, the authors propose a method which eliminates erroneous DGPS measurement data when odometry robot position is fused, and confirm the validity of this approach.

Outdoor navigation of a mobile robot between buildings based on DGPS and odometry data fusion

This paper describes outdoor navigation for a mobile robot by using differential GPS (DGPS) and odometry in a campus walkway environment. The robot position is estimated by fusion of DGPS and odometry. The GPS receiver measures its position by radio waves from GPS satellites. The error of GPS measurement data increases near high buildings and trees because of multi-path and forward diffractions. Thus, it is necessary to pick up only accurate DGPS measurement data when the robot position is modified by fusing DGPS and odometry. In this paper, typical DGPS measurement data observed near high buildings and trees are reported. Then, the authors propose a novel position correction method by fusing GPS and odometry. Fusion of DGPS and odometry is realized using an extended Kalman filter framework. Moreover, outdoor navigation for a mobile robot is accomplished by using the proposed correction method.

Differential GPS and odometry-based outdoor navigation of a mobile robot

To monitor multiple moving objects from a robot in motion is an essential technology in robotic application areas including service and security for human daily life. For this, a method to track multiple walking humans using a mobile robot "in motion" with Laser Range Finder (LRF) is investigated in this paper. Geometric characteristics of human legs are considered to detect their position from the LRF data. Frequency and phase of walking motion are extracted using a pendulum model of the angle between two legs and extended Kalman filter. The algorithm with human walking model anticipates the position of moving humans. The effectiveness of the proposed method is also evaluated with some experiments to track multiple walking humans in indoor environment. An experimental test-bed which consists of a mobile robot 'Yamabico' and a LRF is employed to track people. Resultant experiments and analysis showed that multiple walking people are tracked well from a mobile robot with the proposed method.

People Tracking Using a Robot in Motion with Laser Range Finder

This paper describes an implementation of a mobile robot system for autonomous navigation in outdoor concurred walkways. The task was to navigate through nonmodified pedestrian paths with people and bicycles passing by. The robot has multiple redundant sensors, which include wheel encoders, an inertial measurement unit, a differential global positioning system, and four laser scanner sensors. All the computation was done on a single laptop computer. A previously constructed map containing waypoints and landmarks for position correction is given to the robot. The robot system's perception, road extraction, and motion planning are detailed. The system was used and tested in a 1-km autonomous robot navigation challenge held in the City of Tsukuba, Japan, named “Tsukuba Challenge 2007.” The proposed approach proved to be robust for outdoor navigation in cluttered and crowded walkways, first on campus paths and then running the challenge course multiple times between trials and the challenge final. The paper reports experimental results and overall performance of the system. Finally the lessons learned are discussed. The main contribution of this work is the report of a system integration approach for autonomous outdoor navigation and its evaluation. © 2009 Wiley Periodicals, Inc.

Takashi Tsubouchi

Papers

A 3-D Scan Matching using Improved 3-D Normal Distributions Transform for Mobile Robotic Mapping

Outdoor navigation of a mobile robot between buildings based on DGPS and odometry data fusion

Differential GPS and odometry-based outdoor navigation of a mobile robot

People Tracking Using a Robot in Motion with Laser Range Finder

Autonomous robot navigation in outdoor cluttered pedestrian walkways