Mobile robot navigation

About: Mobile robot navigation is a research topic. Over the lifetime, 14713 publications have been published within this topic receiving 263092 citations.

Robot navigation in dense human crowds: the case for cooperation

Abstract: We consider mobile robot navigation in dense human crowds. In particular, we explore two questions. Can we design a navigation algorithm that encourages humans to cooperate with a robot? Would such cooperation improve navigation performance? We address the first question by developing a probabilistic predictive model of cooperative collision avoidance and goal-oriented behavior by extending the interacting Gaussian processes approach to include multiple goals and stochastic movement duration. We answer the second question with an extensive quantitative study of robot navigation in dense human crowds (488 runs completed), specifically testing how cooperation models effect navigation performance. We find that the “multiple goal” interacting Gaussian processes algorithm performs comparably with human teleoperators in crowd densities near 1 person/m2, while a state of the art noncooperative planner exhibits unsafe behavior more than 3 times as often as this multiple goal extension, and more than twice as often as the basic interacting Gaussian processes. Furthermore, a reactive planner based on the widely used “dynamic window” approach fails for crowd densities above 0.55 people/m2. Based on these experimental results, and previous theoretical observations, we conclude that a cooperation model is important for safe and efficient robot navigation in dense human crowds.

Path planning and guidance techniques for an autonomous mobile cleaning robot

Abstract: In the past mobile robot research was often focused on various kinds of point-to-point transportation tasks. Mobile robot application in service tasks, however, requires quite different path planning and guidance approaches. This paper introduces and discusses in detail specific planning and guidance techniques for a mobile floor-cleaning robot. A kinematic and geometric model of the robot and the cleaning units as well as a 2D-map of the indoor environment are used for planning an appropriate cleaning path. The path is represented by a concatenation of two kinds of typical motion patterns. Each pattern is defined by a sequence of discrete cartesian intermediate goal frames. These frames represent position and orientation of the vehicle and must be translated into motion commands for the robot. The steps of this semi-automatic path planning system are illustrated by a typical cleaning environment. Vehicle guidance includes execution of the planned motion commands, estimation of the robot location, path tracking, as well as detection of and reaction to (isolated) obstacles. For location estimation a least-squares fitting of corresponding geometric contours from the 2D-environment map and geometric 2D-sensor data is used. Obstacle detection is accomplished by testing geometric 2D-sensor data to be part of the preplanned cleaning path. Path planning and parts of the developed vehicle guidance system have been tested with the experimental mobile robot MACROBE. Results reported in this paper demonstrate the efficiency of the described planning, location estimation and path tracking procedures in basic floor-cleaning tasks. >

Composition of local potential functions for global robot control and navigation

Abstract: This paper develops a method of composing simple control policies, applicable over a limited region in a dynamical system's free space, such that the resulting composition completely solves the navigation and control problem for the given system operating in a constrained environment. The resulting control policy deployment induces a global control policy that brings the system to the goal, provided that there is a single connected component of the free space containing both the start and goal configurations. In this paper, control policies for both kinematic and simple dynamical systems are developed. This work assumes that the initial velocities are somewhat aligned with the desired velocity vector field. We conclude by offering an outline of an approach for accommodating arbitrary dynamical constraints and initial conditions.

A Social Robot that Stands in Line

Abstract: Recent research in mobile robot navigation make it feasible to utilize autonomous robots in service fields. But, such applications require more than just navigation. To operate in a peopled environment, robots should recognize and act according to human social behavior. In this paper, we present the design and implementation of one such social behavior: a robot that stands in line much as people do. The system employs stereo vision to recognize lines of people, and uses the concept of personal space for modeling the social behavior. Personal space is used both to detect the end of a line and to determine how much space to leave between the robot and the person in front of it. Our model of personal space is based on measurements from people forming lines. We demonstrate our ideas with a mobile robot navigation system that can purchase a cup of coffee, even if people are waiting in line for service.