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Virginia Tech is Conducting Research on Movement Systems for Robot Dogs

Researchers from Virginia Tech are attempting to make robot dogs move more like animals. The robot dogs' improved movement system operates by using algorithms and sensors that give the robot a more organic movement system. The new movement system uses algorithms to simulate movement patterns of vertebrates, where balance is controlled using neurons in the spinal cord. The robot dogs are also equipped with LiDAR as well as cameras that help it avoid potential collisions with objects in its environment.

Currently, the researchers are using what is called Ghost Robot designs, which are equipped with sensors in order to test new algorithms. One of the researchers, Kavel Hamed, indicated that the project is currently attempting to hone the algorithms in order to make the system perform better.
Trend Themes
1. Organic Movement Systems - Research into simulating organic movement patterns for robots presents opportunities for more lifelike and efficient robotics systems.
2. Collision Avoidance Sensors - Development of advanced LiDAR and camera systems to detect and avoid objects paves the way for safer automated industries.
3. Ghost Robotics - Using Ghost Robot designs equipped with sensors to test new algorithms presents opportunities for more complex and advanced robotics systems.
Industry Implications
1. Robotics Industry - Adoption of organic movement systems and collision avoidance sensors presents opportunities for more advanced robotics systems that are safer and efficient.
2. Automotive Industry - Advancements in collision avoidance sensors and organic movement systems present opportunities for improved autonomous vehicle technology.
3. Agriculture Industry - Implementation of advanced robotics systems, equipped with organic movement systems and collision avoidance sensors, could revolutionize the way farming is done.

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