首页|New Findings in Robotics Described from Northwestern Polytechnic University (Terrain-adaptive Locomotion Control for an Underwater Hexapod Robot: Sensing Leg-terrain Interaction With Proprioceptive Sensors)
New Findings in Robotics Described from Northwestern Polytechnic University (Terrain-adaptive Locomotion Control for an Underwater Hexapod Robot: Sensing Leg-terrain Interaction With Proprioceptive Sensors)
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NETL
NSTL
IEEE
Researchers detail new data in Robotics. According to news originating from Xi'an, People's Republic of China, by NewsRx correspondents, research stated, “An underwater hexapod robot, driven by six C-shaped legs and eight thrusters, has the potential to traverse diverse terrains with unknown deformable properties, which can lead to unknown leg-terrain interaction forces. However, it is hard to use exteroceptive sensors such as cameras and sonars to recognize these properties.” Funders for this research include National Natural Science Foundation of China (NSFC), Doctorate Foundation of Northwestern Polytechnical University. Our news journalists obtained a quote from the research from Northwestern Polytechnic University, “Here we propose a method to perceive the interaction forces and feed them into a controller for determining thrust inputs. The key idea lies in using supervised learning to obtain the properties from reliable proprioceptive sensory data. First, we propose a new expression called zero moment point (ZMP) bias that can indirectly represent the leg-terrain interaction force, removing the effects caused by gravity, buoyancy, and thrust. Second, we gather a walking cycle's discrete ZMP biases and then parameterize them as polynomials. Third, we use several previous walking cycles' parameterized biases to predict the current walking cycle's biases to generate the needed pitch and roll moments. Finally, we propose a terrain-adaptive locomotion controller for the robot, which incorporates these moments into a base control module and uses thrust to compensate for the interaction force for smooth walking.”
Xi’anPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningRobotRoboticsNorthwestern Polytechnic University
NETL
NSTL
IEEE
