• 한국정밀공학회지
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• 제24권1호
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• pp.27-36
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• 2007

This paper describes the development of 6-axis ankle force/moment sensor for the intelligent feet of a humanoid robot. When the robot walks on uneven terrain, the feet should perceive the applied forces Fx, Fy, Fz and moments Mx, My, Mz from the attached 6-axis force/moment sensor on their ankles. Papers have already been published have some disadvantages in the size of the sensor, the rated output and so on. The rated output of each component sensor (6-axis ankle force/moment sensor) is very important to design the 6-axis force/moment sensor for precision measurement. Therefore, each sensor should be designed to get the similar rated output under each rated load. Also, the size of the sensor is very important for mounting to robot's feet. Therefore, the diameter should be below 100 mm and the height should be below 40mm. In this paper, first, the structure of a 6-axis ankle force/moment sensor was modeled for a humanoid robot's feet newly, Second, the equations to predict the strains on the sensing elements was derived, third, the size of the sensing elements was designed by using the equations, then, the sensor was fabricated by attaching straingages on the sensing elements, finally, the characteristic test of the developed sensor was carried out. The rated outputs from the derived equations agree well with the results from the experiments. The interference error of the sensor is less than 2.94%.

• 한국지능시스템학회논문지
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• 제24권4호
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• pp.450-456
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• 2014

휴머노이드 로봇은 인간-로봇 상호작용에 가장 효과적인 로봇 플랫폼이지만 20개 이상의 관절로 구성되어 있을 만큼 복잡한 구조여서 전통적인 역기구학적 방법으로 안정되면서도 정교한 자세를 생성하기가 어렵다. 본 논문에서는 고속 연산최적화 기법인 Particle Swarm Optimization 기법을 사용해서 앞쪽 지면에 놓인 물체를 단측지지 상태로 상체를 굽혀서 왼팔이나 오른팔로 집는 고난도의 자세를 생성하고, 이를 상용 휴머노이드 로봇 플랫폼에 적용하여 검증함으로써 제안 된 방법의 적용 가능성을 확인한다.

• 한국정밀공학회지
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• 제25권7호
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• pp.79-86
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• 2008

This paper describes the development of wearing intelligent shoe system to measure applied forces and moments (ground reaction forces and moments) on the soles of feet during human walking. In order to walk safely, robot must get the intelligent feet with 6-axis force/moment sensors (Fx sensor (x-direction force sensor), Fy sensor, Fz sensor, Mx sensor (Mx : x-direction moment sensor), My sensor, and Mz sensor) and detect the forces and moments data from the sensors. And the feet must be controlled with the data and controllers. While a human is walking, the forces and moments should be measured and analyzed for robot's intelligent feet. Therefore, the wearing intelligent shoe system should be developed. In this paper, four 6-axis farce/moment sensors and two high speed measuring devices were designed and fabricated, and the wearing intelligent shoe system was made using these. The characteristic tests of the wearing intelligent shoe system were performed, and the forces and moments were detected using it.

• 한국지능시스템학회논문지
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• 제23권1호
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• pp.51-56
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• 2013

이족 보행 로봇을 실생활에 적용하기 위해서는 다양한 환경에서의 강인한 보행 뿐만 아니라, 현재 위치를 인식하여 목표 위치로의 경로를 생성하고, 경로를 추종하는 기능이 요구된다. 최근에 많이 사용되고 있는 RFID는 이동 로봇의 위치인식 및 경로 생성에 손쉽게 활용이 가능하다. 그러나 이족 로봇은 보행시에 불안정성을 내포하고 있어 주어진 경로에서 벗어나기 쉽다. 본 논문에서는 FSR(Force Sensing Resistor)센서, 자이로와 가속도 센서를 이용하여 이족 보행 로봇의 보행 안정화 방법을 제안하였다. 또한 양발에 RFID 센서를 장착하여 이족 보행 로봇의 위치 인식 후 경로를 추종하는 알고리즘을 제안하였다. 제안된 보행 안정화 알고리즘은 실제 제작된 이족 보행 로봇을 이용하여 비평탄 지형에서 실험하여 검증하였으며, 경로 추종 실험은 RFID센서를 로봇의 발바닥에 장착하여 평탄 지형에서 보행실험을 통해 검증하였다.

• ETRI Journal
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• 제40권4호
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• pp.522-530
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• 2018

In this study, we developed a robotic walker that actively controls its speed and direction of movement according to the user's gait intention. Sensor fusion between a low-cost light detection and ranging (LiDAR) sensor and inertia measurement units (IMUs) helps determine the user's gait intention. The LiDAR determines the walking direction by detecting both knees, and the IMUs attached on each foot obtain the angular rate of the gait. The user's gait intention is given as the directional angle and the speed of movement. The two motors in the robotic walker are controlled with these two variables, which represent the user's gait intention. The estimated direction angle is verified by comparison with a Kinect sensor that detects the centroid trajectory of both the user's feet. We validated the robotic walker with an experiment by controlling it using the estimated gait intention.