Cédric Pradalier

Experiments in Autonomous Reversing of a Tractor-Trailer System

Trailer reversing is a problem frequently considered in the literature, usually with fairly complex non-linear control theory based approaches. In this paper, we overview our simple method for stabilizing a tractor-trailer system to a trajectory based on the notion of controlling the hitch-angle of the trailer rather than the steering angle of the tractor. The performance of this control method, as implemented on the CSIRO Autonomous Tractor, is then experimentally compared against a number of human drivers, showing that this method performs as well as a moderately skilled human driver, even though the system is significantly handicapped in terms of steering actuation speed and by errors in localization.

Occupancy Grids from Stereo and Optical Flow Data

In this paper, we propose a real-time method to detect obstacles using theoretical models of the ground plane, first in a 3D point cloud given by a stereo camera, and then in an optical flow field given by one of the stereo pair’s camera.

Autonomous Hot Metal Carrier - Navigation and Manipulation with a 20 tonne industrial vehicle

This paper reports work on the automation of a hot metal carrier, which is a 20 tonne forklift-type vehicle used to move molten metal in aluminium smelters. To achieve efficient vehicle operation, issues of autonomous navigation and materials handling must be addressed. We present our complete system and experiments demonstrating reliable operation. One of the most significant experiments was five-hours of continuous operation where the vehicle travelled over 8 km and conducted 60 load handling operations. Finally, an experiment where the vehicle and autonomous operation were supervised from the other side of the world via a satellite phone network are described.

Autonomous Hot Metal Carrier

This paper reports work involved with the automation of a hot metal carrier - a 20 tonne forklift-type vehicle used to move molten metal in aluminium smelters. To achieve efficient vehicle operation, issues of autonomous navigation and materials handling must be addressed. We present our complete system and experiments demonstrating reliable operation. One of the most significant experiments was five-hours of continuous operation where the vehicle travelled over 8 km and conducted 60 load handling operations. We also describe an experiment where the vehicle and autonomous operation were supervised from the other side of the world via a satellite phone network.

Robust Vision-Based Underwater Target Identification and Homing Using Self-Similar Landmarks

Next generation Autonomous Underwater Vehicles (AUVs) will be required to robustly identify underwater targets for tasks such as inspection, localisation and docking. Given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods, however, reliable target segmentation often plagues these systems. This paper addresses robust vision-based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on Self-Similar Landmarks (SSL) that enables robust target pose estimation with respect to a single camera. These algorithms are applied to an AUV with controllers developed for vision-based docking with the target. Experimental results show that system performs exceptionally on limited processing power and demonstrates how the combined vision and controller systems enables robust target identification and docking in a variety of operating conditions.

A simple and efficient control scheme to reverse a tractor-trailer system on a trajectory

Trailer reversing is a problem frequently considered in the literature, usually with fairly complex non-linear control theory based approaches. In this paper, we present a simple method for stabilizing a tractor-trailer system to a trajectory based on the notion of controlling the hitch-angle of the trailer rather than the steering angle of the tractor. The method is intuitive, provably stable, and shown to be viable through various experimental results conducted on our test platform, the CSIRO autonomous tractor.

The Bayesian Occupation Filter

Perception of and reasoning about dynamic environments is pertinent for mobile robotics and still constitutes one of the major challenges. To work in these environments, the mobile robot must perceive the environment with sensors; measurements are uncertain and normally treated within the estimation framework. Such an approach enables the mobile robot to model the dynamic environment and follow the evolution of its environment. With an internal representation of the environment, the robot is thus able to perform reasoning and make predictions to accomplish its tasks successfully. Systems for tracking the evolution of the environment have traditionally been a major component in robotics. Industries are now beginning to express interest in such technologies. One particular example is the application within the automotive industry for adaptive cruise control (Coue et al., 2002), where the challenge is to reduce road accidents by using better collision detection systems. The major requirement of such a system is a robust tracking system. Most of the existing target-tracking algorithms use an object-based representation of the environment. However, these existing techniques must explicitly consider data association and occlusion. In view of these problems, a grid-based framework, the Bayesian occupancy filter (BOF) (Coueet al., 2002, 2003), has been proposed.

Vision-Based Handling Tasks for an Autonomous Outdoor Forklift

In the aluminium industry, Hot Metal Carriers (HMCs) perform the task of transporting molten aluminium from the smelter (where the aluminium is made) to the casting shed where it is turned into block products. The vehicles weigh approximately 20 tonnes unloaded and resemble forklifts except they have a dedicated hook for manipulating the load, called the crucible. In the perspective of a full automation of this kind of vehicle, this paper main contribution is the implementation of robust outdoor crucible handling capacities, relying on the autonomous tracking of especially designed fiducials attached to the crucible handle.

Expressing Bayesian Fusion as a Product of Distributions: Application to Randomized Hough Transform

Data fusion is a common issue of mobile robotics, computer assisted medical diagnosis or behavioral control of simulated character for instance. How- ever data sources are often noisy, opinion for experts are not known with absolute precision, and motor commands do not act in the same exact manner on the envi- ronment. In these cases, classic logic fails to manage efficiently the fusion process. Confronting different knowledge in an uncertain environment can therefore be ade- quately formalized in the bayesian framework. Besides, bayesian fusion can be expensive in terms of memory usage and processing time. This paper precisely aims at expressing any bayesian fusion process as a product of probability distributions in order to reduce its complexity. We first study both direct and inverse fusion schemes. We show that contrary to direct models, inverse local models need a specific prior in order to allow the fusion to be computed as a product. We therefore propose to add a consistency variable to each local model and we show that these additional variables allow the use of a product of the local distributions in order to compute the global probability distribution over the fused variable. Finally, we take the example of the Randomized Hough Transform. We rewrite it in the bayesian framework, considering that it is a fusion process to extract lines from couples of dots in a picture. As expected, we can find back the expression of the Randomized Hough Transform from the literature with the appropriate assumptions.

The CyCab : Bayesian Navigation on Sensory–Motor Trajectories

Autonomous navigation of a mobile robot is a widely studied problem in the robotics community. Most robots designed for this task are equipped with onboard sensor(s) to perceive the external world (sonars, laser telemeters, camera). Two main approaches to autonomous navigation have been proposed: reactive navigation, where the robot uses only its current perceptions to move and explore without colliding (e.g. Arkin (1998) or Bonasso et al. (1995)), and servoed navigation, in which the robot is given a preplanned reference trajectory and uses some closed-loop control law to follow it (e.g. Laumond et al. (1989) or Lamiraux et al. (1999)). In servoed problems, two classes of approaches can again be separated: state-space tracking (e.g. Hermosillo et al. (2003b,a)) and perception- space tracking (e.g. Malis et al. (2001) or Chaumette (1994)).