ICRA 2011 Paper Abstract


Paper TuP103.1

Jalgha, Bassam (American University of Beirut), Asmar, Daniel (American University of Beirut), Elhajj, Imad (American University of Beirut)

A Hybrid Ankle/Hip Preemptive Falling Scheme for Humanoid Robots

Scheduled for presentation during the Regular Sessions "Humanoid Robots I" (TuP103), Tuesday, May 10, 2011, 13:40−13:55, Room 3D

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on March 30, 2020

Keywords Humanoid Robots, Robot Safety, Humanoid and Bipedal Locomotion


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.



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