Judson P. Jones

Navigation using range images on a mobile robot

Abstract We describe an integrated navigation system for an autonomous mobile robot using a laser range camera to obtain knowledge about the environment. The implemented system maintains a 2D world model (floor map) by integrating knowledge obtained from several range images acquired as the robot moves around in its attempt to find a path to the goal position. A path planner uses the floor map to generate collision-free paths consisting of sequences of configurations. Car-like kinematic constraints ensure smooth paths that can be send directly to a wheel controller. The system was implemented on the HERMIES-III robot, a vehicle with 3 degrees of freedom, and tested in both laboratory and simulated environments. These tests showed that a simple integration of the environment modeler and the path planner provides the robot with basic explorative and navigational capabilities. In particular, the system is capable of performing total re-planning in cases where the initial path to the goal point turns out to be blocked.

DEMO 89-the initial experiment with the HERMIES-III robot

HERMIES-III is a large mobile robot designed for human-scale experiments. The initial experiment with the robot (DEMO 89) was the cleanup of a simulated chemical spill. To perform the experiment, the robot was required to plan a path through an already known world, navigate along the path (avoiding unexpected obstacles), and locate and remove debris from a target area. A description is given of the software system that was developed to perform the experiment. The software system consisted of 19 processes that operated on a distributed set of heterogeneous computers.<<ETX>>

Rapid world modelling from a mobile platform

The ability to successfully use and interact with a computerized world model is dependent on the ability to create an accurate world model. The goal of this project was to develop a prototype system to remotely deploy sensors into a workspace, collect surface information, and rapidly build an accurate world model of that workspace. A key consideration was that the workspace areas are typically hazardous environments, where it is difficult or impossible for humans to enter. Therefore, the system needed to be fully remote, with no external connections. To accomplish this goal, an electric, mobile platform with battery power sufficient for both the platform and sensor electronics was procured and 3D range sensors were deployed on the platform to capture surface data within the workspace. A radio Ethernet connection was used to provide communications to the vehicle and all on-board electronics. Video from on-board cameras was also transmitted to the base station and used to teleoperate the vehicle. Range data generated by the on-board 3D sensors was transformed into surface maps, or models. Registering the sensor location to a consistent reference frame as the platform moved through the workspace allowed construction of a detailed 3D world model of the extended workspace.

A system for simulating shared memory in heterogeneous distributed-memory networks with specializations for robotics applications

Hetero Helix is a programming environment which simulates shared memory on a heterogeneous network of distributed-memory computers. The machines in the network may vary with respect to their native operating systems and internal representation of numbers. Hetero Helix presents a simple shared memory programming model to developers, and considers the needs of designers, system integrators and maintainers. The key software technology in Hetero Helix is a compiler which automatically generates code for translating data representations from the format native to each machine into a common format and vice versa. The design of Hetero Helix was motivated by the requirements of robotics applications.<<ETX>>

Concurrent algorithms for a mobile robot vision system

The application of computer vision to mobile robots has generally been hampered by insufficient on-board computing power. The advent of VLSI-based general purpose concurrent multiprocessor systems promises to give mobile robots an increasing amount of on-board computing capability, and to allow computation intensive data analysis to be performed without high-bandwidth communication with a remote system.

Modular control architecture for real-time synchronous and asynchronous systems

This paper describes a control architecture for real-time control of complex robotic systems. The modular integrated control architecture (MICA), which is actually two complementary control systems, recognizes and exploits the differences between asynchronous and synchronous control. The asynchronous control system simulates shared memory on a heterogeneous network. For control information, a portable event-scheme is used. This scheme provides consistent interprocess coordination among multiple tasks on a number of distributed systems. The machines in the network can vary with respect to their native operating systems and the internal representation of numbers they use. The synchronous control system is needed for tight real-time control of complex electromechanical systems such as robot manipulators, and the system uses multiple processors at a specified rate. Both the synchronous and asynchronous portions of MICA have been developed to be extremely modular. MICA presents a simple programming model to code developers and also considers the needs of system integrators and maintainers. MICA has been used successfully in a complex robotics project involving a mobile 7-degree-of-freedom manipulator in a heterogeneous network with a body of software totaling over 100,000 lines of code. MICA has also been used in another robotics system, controlling a commercial long-reach manipulator.

Real-time construction of three-dimensional occupancy maps

An experimental study of parallel algorithms for constructing 3-D occupancy maps is described. Data from a laser range camera are processed on an iWarp parallel computer. The resulting 3-D map is rendered using raytracing. The construction and rendering consume less than 800 ms.<<ETX>>

Spatial Reasoning In The Treatment Of Systematic Sensor Errors

In processing ultrasonic and visual sensor data acquired by mobile robots systematic errors can occur. The sonar errors include distortions in size and surface orientation due to the beam resolution, and false echoes. The vision errors include, among others, ambiguities in discriminating depth discontinuities from intensity gradients generated by variations in surface brightness. In this paper we present a methodology for the removal of systematic errors using data fror the sonar sensor domain to guide the processing of information in the vision domain, and vice versa. During the sonar data processing some errors are removed from 2D navigation maps through pattern analyses and consistent-labelling conditions, using spatial reasoning about the sonar beam and object characteristics. Others are removed using visual information. In the vision data processing vertical edge segments are extracted using a Canny-like algorithm, and are labelled. Object edge features are then constructed from the segments using statistical and spatial analyses. A least-squares method is used during the statistical analysis, and sonar range data are used in the spatial analysis.

Design and Implementation of Two Concurrent Multi-Sensor Integration Algorithms for Mobile Robotsl

Two multi-sensor integration algorithms useful in mobile robotics applications are reviewed. A minimal set of utilities are then developed which enable implementation of these algorithms on a distributed memory concurrent computer.

Real-time construction and rendering of three-dimensional occupancy maps

This paper describes a preliminary sensory system for real-time sensor-based navigation in a three-dimensional, dynamic environment. Data from a laser range camera are processed on an iWarp parallel computer to create a 3-D occupancy map. This map is rendered using raytracing. The construction and rendering consume less than 800 milliseconds.