Model-based estimation of off-highway road geometry using single-axis LADAR and inertial sensing

This paper applies some previously studied extended Kalman filter techniques for planar road geometry estimation to the domain of autonomous navigation of off-highway vehicles. In this work, a clothoid model of the road geometry is constructed and estimated recursively based on road features extracted from single-axis LADAR range measurements. We present a method for feature extraction of the road centerline in the image plane, and describe its application to recursive estimation of the road geometry. We analyze the performance of our method against simulated motion of varied road geometries and against closed-loop detection, tracking and following of desert roads. Our method accomodates full 6 DOF motion of the vehicle as it navigates, constructs consistent estimates of the road geometry with respect to a fixed global reference frame, and requires an estimate of the sensor pose for each range measurement

A new approach to teaching feedback

The Control and Dynamical Systems (CDS) Department at the California Institute of Technology (Caltech) has revised its entry-level curriculum in dynamics, feedback, and control with the goals of updating the subject matter to include modern tools and making control tools accessible to a nontraditional audience. One of the approaches made was to divide the introductory control theory class into two tracks, with a conceptual track geared toward students who need only a conceptual overview of control tools and an analytical track providing a more detailed mathematical treatment of feedback. The conceptual track, CDS 101, which is mainly discussed in the paper, is intended for advanced students in science and engineering who can benefit from an overview of control techniques but who might not have the need for the mathematical depth underlying the material. Special attention is paid to ensuring that the course is accessible to students from biological, physical, and information sciences, using examples from these domains to illustrate concepts. The goal of the course is to enable students to use the principles and tools of feedback in their research activities

The Caltech Multi-Vehicle Wireless Testbed

In this paper we introduce the Caltech Multi-Vehicle Wireless Testbed (MVWT), a platform for testing decentralized control methodologies for multiple vehicle coordination and formation stabilization. The testbed consists of eight mobile vehicles, an overhead vision system providing GPS-like position information and wireless Ethernet for communications. Each vehicle rests on omni-direction casters and is powered by two high-performance ducted fans. Thus, a unique feature of our testbed is that the vehicles have second order dynamics, requiring real-time feedback algorithms to stabilize the system while performing cooperative tasks. The testbed will be used by various research groups at Caltech and elsewhere as a means to validate theoretical advances in multiple-vehicle coordination and control, networked control systems, real time networking and high confidence distributed computation

A Platform for Cooperative and Coordinated Control of Multiple Vehicles: The Caltech Multi-Vehicle Wireless Testbed

The Caltech Multi-Vehicle Wireless Testbed (MVWT) is an experimental platform for investigating the increasingly important intersecting frontiers of reliable distributed computation, communication and control. The testbed consists of eight autonomous vehicles equipped with onboard sensing, communication and computation. The vehicles are underactuated and exhibit nonlinear second-order dynamics, key properties that capture the essence of similar real-world applications at the forefront of cooperative control