Akinori Sekiguchi

The efficacy of symmetric cognitive biases in robotic motion learning

We propose an application of human-like decision-making to robotic motion learning. Human is known to have illogical symmetric cognitive biases that induce “if p then q” and “if not q then not p” from “if q then p.” The loosely symmetric Shinohara model quantitatively represents the tendencies (Shinohara et al. 2007). Previous studies one of the authors have revealed that an agent with the model used as the action value function shows great performance in n-armed bandit problems, because of the illogical biases. In this study, we apply the model to reinforcement learning with Q-learning algorithm. Testing the model on a simulated giant-swing robot, we have confirmed its efficacy in convergence speed increase and avoidance of local optimum.

Motion analysis for a three-wheeled walker by using motion sensor

In this paper, we analyzed gait motions with a prototype of a walking assist device “Raku-WALK”, for evaluation of the device. The Raku-WALK is a three-wheeled walker which can be used in sitting position. Using 9-axis motion sensors, gait motions with the Raku-WALK along a straight path and a circular path were measured and analyzed, when the rear caster of the Raku-WALK is pivotable, or is not pivotable. From the results, when the rear caster is pivotable, rotational motions of the Raku-WALK and the waist, which were different from natural rotation of the waist during normal gait motion, were observed.

A study on effect of two-arch structure of foot for biped robots

The arch structure of human foot plays important roles such as impact absorption for bipedal locomotion. In this paper, the two-arch structure is introduced into the foot model of biped robot. Using a flat foot model, a one-arch foot model and the two-arch foot model, simulations of robot motion are performed by ODE and effects of the arch structure are verified. When the inner arch was softer than the outer arch like human, the robot motion such that the COG returns to inner direction was observed. It was verified that the property of the returning motion was determined by the difference of elasticities between the inner arch and the outer arch, and the property of motion in the frontal direction was determined by the average of elasticities.

A Walking Pattern Generator Using a Spherical Inverted Pendulum with an Underfloor Pivot(Mechanical Systems)

Humans utilize the configuration with extended knees to achieve efficient walk. A humanoid robot, however, cannot do so, since this posture is a singular configuration. In order to tackle this problem, in our previous work, a walking pattern generator based on the spherical inverted pendulum model has been proposed. It enables to generate up-and-down waist motions and utilizes the singularity neighborhood in the middle of each support phase. However, the spherical inverted pendulum model cannot move the ZMP during each single support phase. In this paper, we propose a new approach to generate a walking pattern based on a Spherical Inverted Pendulum model with an Underfloor Pivot (the SIPUP method). With this method, the ZMP gains mobility during each single-leg support phase, and walking with a smaller acceleration is achieved. In addition, it becomes easy to utilize the singularity neighborhood. As a result, the knee joint can be almost fully extended (less than 0.01 rad). Experimental results show the effectiveness of our approach.