Showing papers by "William Whittaker published in 2006"
TL;DR: A robust approach to navigating at high speed across desert terrain using a combination of LIDAR and RADAR based perception sensors and a human‐based preplanning system to improve reliability and robustness is presented.
Abstract: This article presents a robust approach to navigating at high-speed across desert terrain. A central theme of this approach is the combination of simple ideas and components to build a capable and robust system. A pair of robots were developed which completed a 212 kilometer Grand Challenge desert race in approximately seven hours. A path-centric navigation system uses a combination of LIDAR and RADAR based perception sensors to traverse trails and avoid obstacles at speeds up to 15m/s. The onboard navigation system leverages a human based pre-planning system to improve reliability and robustness. The robots have been extensively tested, traversing over 3500 kilometers of desert trails prior to completing the challenge. This article describes the mechanisms, algorithms and testing methods used to achieve this performance.
144 citations
TL;DR: The challenges, mechanisms, sensing, and software of subterranean robots are presented and results obtained from operations in active, abandoned, and submerged subterranean spaces are shown.
Abstract: Robotic systems exhibit remarkable capability for exploring and mapping subterranean voids. Information about subterranean spaces has immense value for civil, security, and commercial applications where problems, such as encroachment, collapse, flooding and subsidence can occur. Contemporary method for underground mapping, such as human surveys and geophysical techniques, can provide estimates of void location, but cannot achieve the coverage, quality, or economy of robotic approaches. This article presents the challenges, mechanisms, sensing, and software of subterranean robots. Results obtained from operations in active, abandoned, and submerged subterranean spaces will also be shown. © 2006 Wiley Periodicals, Inc.
76 citations
TL;DR: Carnegie Mellon University's Red Team developed two robots, which used a combination of autonomous and human preplanning to become two of only four robots to complete the 2005 DARPA Grand Challenge.
Abstract: The 2005 DARPA Grand Challenge, a 212-kilometer race through the Mojave Desert, showcased the state of the art in high-speed, autonomous navigation of trails and roads. To win the challenge, a team's robot had to complete the course faster than any other robot, and it had to do so within 10 hours. Carnegie Mellon University's Red Team developed two robots, which used a combination of autonomous and human preplanning to become two of only four robots to complete the Grand Challenge. The robots used onboard sensors to adjust a preplanned route to avoid obstacles and correct for position-estimation errors. To be successful, teams had to develop innovative algorithms and systems - and rigorously test them to verify performance. The Red Team used the tests regressively to evaluate how unit changes in hardware and software affected the robots' overall driving ability
3 citations
01 Oct 2006
TL;DR: The mechatronic and software considerations that resulted in two robots that have completed over 4000 km of autonomous navigation of trails and off-road terrain at an average speed of approximately 30km/h, with sustained top speeds of 55 km/h are presented.
Abstract: This paper presents an approach that achieves robust high-speed navigation of prescribed routes. We present the mechatronic and software considerations that resulted in two robots that have completed over 4000 km of autonomous navigation of trails and off-road terrain at an average speed of approximately 30 km/h, with sustained top speeds of 55 km/h
2 citations