Dynamic Obstacle Avoidance
Related: RRVO   Moving Objects  

Current Contributors: Nancy Amato
Project Alumni: Nancy Amato
Interns and undergrad students: Nancy Amato

Supported By: NSF

When it comes to real-world robotics applications, plans must consider and adapt to changes in the environment. A mobile robot performing navigation tasks must update its plan if it encounters a human in its way. A robotic arm that picks and moves several loads must consider how the environment changes as it moves the loads. In multi-robot applications, robots must avoid colliding one each other. Collision avoidance techniques are then essential to develop efficient motion planning algorithms within dynamic environments.

Reciprocally-Rotating Velocity Obstacles (RRVO)

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Planning Motion Among Moving Objects

Planning in an environment with moving objects and no knowledge of the future trajectories of said objects.

Multi-Agent Motion Planning

We show an adaptation of a discrete algorithm to solve the Multi-Agent Motion Planning problem in continuous spaces.