Electronic maneuvering board and dead reckoning tracer decision aid for the officer of the deck
Proceedings of the 2001 annual ACM SIGAda international conference on Ada
Detection, Tracking and Avoidance of Multiple Dynamic Objects
Journal of Intelligent and Robotic Systems
Reactive Pedestrian Path Following from Examples
CASA '03 Proceedings of the 16th International Conference on Computer Animation and Social Agents (CASA 2003)
Autonomous behaviors for interactive vehicle animations
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
A maneuvering-board approach to path planning with moving obstacles
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Survival kit: a constraint-based behavioural architecture for robot navigation
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
Spatial learning for navigation in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Obstacle avoidance in a dynamic environment: a collision cone approach
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Exponential fields formulation for WMR navigation
Applied Bionics and Biomechanics - Personal Care Robotics
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Most autonomous mobile agents operate in a highly constrained environment. Despite significant research, existing solutions are limited in their ability to handle heterogeneous constraints within highly dynamic or uncertain environments. This paper presents a novel maneuver selection technique suited for both 2D and 3D environments with highly dynamic maneuvering constraints and multiple mobile obstacles. Agents may have any arbitrary set of nonholonomic control variables; maneuvers can be constrained by a broad class of function inequalities, including time-dependent constraints involving nonlinear relationships between controlled and agent-state variables. The resulting algorithm has been implemented to run in real time using only a fraction of the CPU's capacity on an ordinary notebook computer and performs well in a number of taxing simulated situations.