Optimal whole body motion planning of humanoid with articulated spine for object manipulation in double support phase

Author(s):  
K. Hari Teja ◽  
Francis James ◽  
Suril V. Shah
2018 ◽  
pp. 1575-1599 ◽  
Author(s):  
Eiichi Yoshida ◽  
Fumio Kanehiro ◽  
Jean-Paul Laumond

Author(s):  
ChangHyun Sung ◽  
Takahiro Kagawa ◽  
Yoji Uno

AbstractIn this paper, we propose an effective planning method for whole-body motions of humanoid robots under various conditions for achieving the task. In motion planning, various constraints such as range of motion have to be considered. Specifically, it is important to maintain balance in whole-body motion. In order to be useful in an unpredictable environment, rapid planning is an essential problem. In this research, via-point representation is used for assigning sufficient conditions to deal with various constraints in the movement. The position, posture and velocity of the robot are constrained as a state of a via-point. In our algorithm, the feasible motions are planned by modifying via-points. Furthermore, we formulate the motion planning problem as a simple iterative method with a Linear Programming (LP) problem for efficiency of the motion planning. We have applied the method to generate the kicking motion of a HOAP-3 humanoid robot. We confirmed that the robot can successfully score a goal with various courses corresponding to changing conditions of the location of an obstacle. The computation time was less than two seconds. These results indicate that the proposed algorithm can achieve efficient motion planning.


Author(s):  
Tara Farizeh ◽  
Mohammad Jafar Sadigh

Dynamic modeling of a biped has gained lots of attention during past few decades. While stability and energy consumption were among the first issues which were considered by researchers, nowadays achieving maximum speed and improving pattern of motion to reach that speed are the important targets in this field. Walking model of bipeds usually includes two phases, single support phase (SSP), in which only the stance foot is in contact with the ground while the opposite leg is swinging; and double support phase (DSP) in which the swing leg is in contact with the ground in addition to the rear foot. It is common in the simplified model of walking to assume the stance leg foot, flat during the entire SSP; but one may know that for human walking, there is also a sub-phase during SSP in which the heel of stance foot leaves the ground while the whole body is supported by toe link. Actually in this sub phase the stance leg foot rotates around the toe joint. This paper is trying to study the effect of toe-link and heel to toe walking model on dynamic and specially speed of walking compare to flat foot model.


2020 ◽  
Vol 14 ◽  
Author(s):  
Liyu Cao ◽  
Xinyu Chen ◽  
Barbara F. Haendel

Experiments in animal models have shown that running increases neuronal activity in early visual areas in light as well as in darkness. This suggests that visual processing is influenced by locomotion independent of visual input. Combining mobile electroencephalography, motion- and eye-tracking, we investigated the influence of overground free walking on cortical alpha activity (~10 Hz) and eye movements in healthy humans. Alpha activity has been considered a valuable marker of inhibition of sensory processing and shown to negatively correlate with neuronal firing rates. We found that walking led to a decrease in alpha activity over occipital cortex compared to standing. This decrease was present during walking in darkness as well as during light. Importantly, eye movements could not explain the change in alpha activity. Nevertheless, we found that walking and eye related movements were linked. While the blink rate increased with increasing walking speed independent of light or darkness, saccade rate was only significantly linked to walking speed in the light. Pupil size, on the other hand, was larger during darkness than during light, but only showed a modulation by walking in darkness. Analyzing the effect of walking with respect to the stride cycle, we further found that blinks and saccades preferentially occurred during the double support phase of walking. Alpha power, as shown previously, was lower during the swing phase than during the double support phase. We however could exclude the possibility that the alpha modulation was introduced by a walking movement induced change in electrode impedance. Overall, our work indicates that the human visual system is influenced by the current locomotion state of the body. This influence affects eye movement pattern as well as neuronal activity in sensory areas and might form part of an implicit strategy to optimally extract sensory information during locomotion.


Author(s):  
Kondalarao Bhavanibhatla ◽  
Sulthan Suresh-Fazeela ◽  
Dilip Kumar Pratihar

Abstract In this paper, a novel algorithm is presented to achieve the coordinated motion planning of a Legged Mobile Manipulator (LMM) for tracking the given end-effector’s trajectory. LMM robotic system can be obtained by mounting a manipulator on the top of a multi-legged platform for achieving the capabilities of both manipulation and mobility. To exploit the advantages of these capabilities, the manipulator should be able to accomplish the task, while the hexapod platform moves simultaneously. In the presented approach, the whole-body motion planning is achieved in two steps. In the first step, the robotic system is assumed to be a mobile manipulator, in which the manipulator has two additional translational degrees of freedom at the base. The redundancy of this robotic system is solved by treating it as an optimization problem. Then, in the second step, the omnidirectional motion of the legged platform is achieved with a combination of straight forward and crab motions. The proposed algorithm is tested through a numerical simulation in MATLAB and then, validated on a virtual model of the robot using multibody dynamic simulation software, MSC ADAMS. Multiple trajectories of the end-effector have been tested and the results show that the proposed algorithm accomplishes the given task successfully by providing a singularity-free whole-body motion.


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