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The proposed scene analysis architecture is evaluated through experimental results within a robotic collision avoidance system.
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Many authors have used the optical flow as a starting point for the segmentation of moving objects in many applications under different scenarios such as robotics, collision avoidance, navigation, video coding, and driving assistance.
Besides, a set of metrics and scenarios for benchmarking in multi-robot collision avoidance are proposed.
An approach based on geometric invariance and sliding mode ideas is proposed for redundancy resolution in robotic systems to fulfill configuration and workspace constraints caused by robot mechanical limits, collision avoidance, industrial security, etc.
Autopilot includes traffic-aware cruise control, automatic parallel parking, side collision avoidance and automatic lane changing.
Aside from providing more precise manipulation, closed-loop position updates allow the use of standard macroscale robotic functions such as grasp planning, collision avoidance, and detection, grasping, and payload detection and delivery.
With these events, we define two collision avoidance timings: critical time to avoid collision and preferred time to avoid collision, and they dictate the design of software-based collision avoidance systems.
This avoids the need for collision avoidance algorithms.
Collision avoidance between multiple mobile robots can also be realized.
This paper presents a modern collision avoidance system based on the open-source robotics framework ROS.
Both avoiding motions also satisfied the smooth collision avoidance requirement.
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