Abstract
AbstractMotion planning for mobile robots has been an active area of research in recent years. One reason for this is the increasing importance of applications that take place in unstructured and time‐varying environments—such as outdoor waste management or delivery of food and medicines in a hospital. One of the main difficulties in automating such tasks is combining on‐line sensing with “on the fly” intelligent motion planning. On the other hand, the theoretical work in this area has matured enough to warrant active hardware and experimentation work. Discussed below is an attempt to implement a class of strategies for motion planning with incomplete information. We address the following experimental issues: the robot's ability to cope with limited information available from typical sensors while operating in a cluttered environment with unknown obstacles; handling the registration problem to assess the robot's current location; performing necessary data processing and planning fast enough to assure acceptable motion speeds; and handling situations that require the robot to make loops, retreat, and visit some areas of its path more than once. The results are encouraging; they indicate the feasibility of practical systems capable of operating in a highly complex uncertain environment. © 1994 John Wiley & Sons, Inc.
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