Biologically-inspired push recovery capable bipedal locomotion modeling through hybrid automata

This paper presents a non-verbal and non-facial method for effective communication of a "mechanoid robot" by conveying the emotions through gestures. This research focuses on human-robot interaction using a mechanoid robot that does not possess any anthropomorphic facial features for conveying gestures. Another feature of this research is the use of human-like smooth motion of this mechanoid robot in contrast to the traditional trapezoidal velocity profile for its communication. For conveying gestures, the connection between motion of robot and perceived emotions is established by varying the velocity and acceleration of the mechanoid structure. The selected motion parameters are changed systematically to observe the variation in perceived emotions. The perceived emotions have been further investigated using three different emotional behavior models: Russell's circumplex model of affect, Tellegen-WatsonClark model and PAD model. Results obtained show that the designated motion parameters are linked with the change of emotions. Moreover, the emotions perceived by the user are same through all three models, validating the reliability of all the three emotional scale models and also of the emotions perceived by the user.

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“…This will focus on how to differentiate the gestures which can convey overlapping emotions [70][71][72].…”

Section: Recommendations and Future Workmentioning

confidence: 99%

Interaction of robot with humans by communicating simulated emotional states through expressive movements

Sial

Ayaz

et al. 2016

Intel Serv Robotics

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“…6. In comparison with [15,16], which basically studied automatic gait generation, a stable walking trajectory and a feedback control algorithm are explained in Sect. 7.…”

Section: Introductionmentioning

confidence: 99%

Mechanical and electrical design of a biped humanoid which has multiple motors on each lower body joint

Lee

Park

2015

Intel Serv Robotics

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The design of a biped humanoid that has multiple motors on each lower body joint is described. The joint actuators of the lower body should have high-power performance with compact size for walking while dynamically supporting the entire weight. The authors propose a design method in which multiple motors are installed in a joint. The method can amplify the joint torque and this is verified by experiments involving measurement of the joint angle and the current with respect to the number of motors on a single joint. The mechanical design and control system are explained. The design results are verified from a walking experiment. The proposed design improved the walking performance.

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“…Consequently, correct analytical model and intuitive solutions are difficult to conceive and hard to find [1]. Researchers have tried to make kinematics based biped locomotion models and formulate control strategy corresponding to several subphases of walking gait and tried to develop a controller for entire gait cycle by superimposing the control strategy of the control sub-phases [2]. However, due to non-linearity, the condition of superposition is not appropriate and hence the overall control strategy based on the model failed.…”

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confidence: 99%

Hybrid Model for Passive Locomotion Control of a Biped Humanoid:The Artificial Neural Network Approach

Raj¹,

Semwal²,

Nandi³

2018

IJIMAI

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Developing a correct model for a biped robot locomotion is extremely challenging due to its inherently unstable structure because of the passive joint located at the unilateral foot-ground contact and varying configurations throughout the gait cycle, resulting variation of dynamic descriptions and control laws from phase to phase. The present research describes the development of a hybrid biped model using an Open Dynamics Engine (ODE) based analytical three link leg model as a base model and, on top of it, an Artificial Neural Network based learning model which ensures better adaptability, better limits cycle behaviors and better generalization while negotiating along a down slope. The base model has been configured according to the individual subjects and data have been collected using a novel technique through an android app from those subjects while walking down a slope. The pattern between the deviation of the actual trajectories and the base model generated trajectories has been found using a back propagation based artificial neural network architecture. It has been observed that this base model with learning based compensation enables the biped to better adapt in a real walking environment, showing better limit cycle behaviors. We also observed the bounded nature of deviation which led us to conclude that the strategy for biped locomotion control is generic in nature and largely dominated by learning.

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Biologically-inspired push recovery capable bipedal locomotion modeling through hybrid automata

Cited by 56 publications

References 26 publications

Interaction of robot with humans by communicating simulated emotional states through expressive movements

Interaction of robot with humans by communicating simulated emotional states through expressive movements

Mechanical and electrical design of a biped humanoid which has multiple motors on each lower body joint

Hybrid Model for Passive Locomotion Control of a Biped Humanoid:The Artificial Neural Network Approach

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