Carnegie Mellon Robotics Institute
doctoral dissertation, tech. report CMU-RI-TR-95-42, Robotics Institute, Carnegie Mellon University, December, 1995
|A substantial portion of the Earth is inaccessible to any sort of wheeled mechanism-natural ostacles like large rocks, loose soil, deep ravines, and steep slopes conspire to render rolling locomotion ineffective. Hills, mountains, shores, seabeds, as well as the moon and other planets present similar terrain challenges.
In many of these natural terrains, legs are well suited. They can avoid small obstacles by making discrete contacts and passing up undesirable footholds. Legged mechanisms can climb over obstacles and step over ditches, surmounting terrain discontinuities of body-scale while staying level and stable.
To achieve their potential, legged robots must coordinate their leg motions to climb over, step across and walk natural terrain. These coordinated motions, which support and propel the robot, are called a gait. This thesis develops a new method of gait planning and control that enables statically-stable walking robots to produce a gait that is robust and productive in natural terrain.
Independent task-achieving process, called gait behaviors, establish a nominal gait, adapt it to terrain, and react to disturbances like bumps and slips. Gait controlled in this way enabled the robot Dante II to walk autonomously in natural terrain, including the volcanic crater of Mount Spurr. This method extends to other walking robots as demonstrated by a generalized hexapod that performs the variety of gaits seen in six-legged insects, as well as aperiodic free gaits. The ability to change gait patterns on-the-fly with continuous, stable motion is a new developments that enables robots to behave more like animals in adapting their gait to terrain.
Finally, this thesis describes why walking robots need predictive plans as well as reflexive behaviors to walk effectively in the real world. It presents a method of guiding the behavior of a walking robot by planning distinct attributes of the desired gait. This partitioning of gait planning avoids the complexity of high degree-of-freedom motion planning. The ability to plan and foresee changes in gait improves performance while maintaining robust safety and stability.
Grant ID: H0358021
Number of pages: 130
|David Wettergreen, "Robotic Walking on Natural Terrain: Gait planning and behavior-based control for statically-stable walking robots," doctoral dissertation, tech. report CMU-RI-TR-95-42, Robotics Institute, Carnegie Mellon University, December, 1995|
author = "David Wettergreen",
title = "Robotic Walking on Natural Terrain: Gait planning and behavior-based control for statically-stable walking robots",
booktitle = "",
school = "Robotics Institute, Carnegie Mellon University",
month = "December",
year = "1995",
address= "Pittsburgh, PA",
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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