Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Intelligence without representation
Artificial Intelligence
A dynamical systems perspective on agent-environment interaction
Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
Adaptive Behavior - Special issue on biologically inspired models of navigation
From Living Eyes to Seeing Machines
From Living Eyes to Seeing Machines
Active Perception
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Group behavior from video: a data-driven approach to crowd simulation
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
An efficient system for combined route traversal and collision avoidance
Autonomous Robots
Flying Fast and Low Among Obstacles: Methodology and Experiments
International Journal of Robotics Research
A Minimalistic Model of Visually Guided Obstacle Avoidance and Path Selection Behavior
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
Segmenting Humans from Mobile Thermal Infrared Imagery
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
Temporal stabilization of discrete movement in variable environments: an attractor dynamics approach
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Control and navigation of the skiing robot
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Attractor dynamics approach to formation control: theory and application
Autonomous Robots
Optical flow or image subtraction in human detection from infrared camera on mobile robot
Robotics and Autonomous Systems
Leveraging human behavior models to predict paths in indoor environments
Pervasive and Mobile Computing
Mathematics and Computers in Simulation
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Using a biologically-inspired model, we show how successful route selection through a cluttered environment can emerge from on-line steering dynamics, without explicit path planning. The model is derived from experiments on human walking performed in the Virtual Environment Navigation Lab (VENLab) at Brown. We find that goals and obstacles behave as attractors and repellors of heading, the direction of locomotion, for an observer moving at a constant speed. The influence of a goal on turning rate increases with its angle from the heading and decreases exponentially with its distance; the influence of an obstacle decreases exponentially with angle and distance. Linearly combining goal and obstacle terms allows us to simulate paths through arbitrarily complex scenes, based on information about obstacles in view near the heading direction and a few meters ahead. We simulated the model on a variety of scene configurations and observed generally efficient routes, and verified this behavior on a mobile robot. Discussion focuses on comparisons between dynamical models and other approaches, including potential field models and explicit path planning. Effective route selection can thus be performed on-line, in simple environments as a consequence of elementary behaviors for steering and obstacle avoidance.