In this paper; the problem of motion planning in environments with both known static obstacles and unpredictable dynamic constraints is considered. A methodology is introduced in which the motion plan for the static environment is modified on-line to accommodate the unpredictable constraints in such a way that the completeness properties of the original motion plan are preserved. At the heart of the approach is the idea that Navigation functions are indeed Lyapunov functions; and that the traditional method of forcing the robot to track the negative gradient of field is not the only input which stabilizes the system. This extra freedom in selecting the input is used to accommodate the dynamic constraints. A computational method for selecting the appropriate inputs is given. The method is used to solve two sample problems. The constraints in these cases are used to model collisions with other robots and, in the second example, a team of robots traveling in formation. Finally, some preliminary work on extending the approach to nonholonomic systems is presented. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/meam_papers/13