A Hybrid Ankle/Hip Preemptive Falling Scheme for Humanoid Robots
If we are to one day rely on robots as assistive devices they should be capable of mitigating the impact of random disturbances and avoid falling. Humans are surprisingly apt at remaining on their feet when pushed; they rely on reflexes such as bending the ankles and/or the hips, or by taking a step if the magnitude of the disturbance is relatively large. This paper presents a fall avoidance scheme that is capable of applying both ankle and hip strategies on a humanoid robot. While both strategies serve the same purpose, the hip strategy can absorb larger disturbances but has a higher energy overhead and should be avoided when it is not necessary. Our system is capable of detecting at the onset of a disturbance if an ankle or hip strategy is more appropriate. The decision is taken based on a ‘decision surface’ that is delimited by threshold values of the robot’s state variables. The control is based on the intuitive Virtual Model Control (VMC) approach. The system is tested on a simulated robot developed under Gazebo. Results show successful fall avoidance with an ability to choose the optimum fall avoidance strategy.
Bassam Jalgha Daniel Asmar Imad Elhajj
Faculty of Engineering and Architecture,Mechanical Engineering,American University of Beirut,1107 20 Facutly of Engineering and Architecture,Electrical and Computer Engineering,American University of B
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
1256-1262
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）