Behind the Game

When playing inter-personal sports games remotely, the time lag between user actions and feedback decreases the user’s performance and sense of agency. While computational assistance can improve performance, naive intervention independent of the context also compromises the user’s sense of agency. We propose a context-aware assistance method that retrieves both user performance and sense of agency, and we demonstrate the method using air hockey (a two-dimensional physical game) as a testbed. Our system includes a 2D plotter-like machine that controls the striker on half of the table surface, and a web application interface that enables manipulation of the striker from a remote location. Using our system, a remote player can play against a physical opponent from anywhere through a web browser. We designed the striker control assistance based on the context by computationally predicting the puck’s trajectory using a real-time captured video image. With this assistance, the remote player exhibits an improved performance without compromising their sense of agency, and both players can experience the excitement of the game.

publication:

• Azumi Maekawa, Hiroto Saito, Narin Okazaki, Shunichi Kasahara, and Masahiko Inami. "Behind The Game: Implicit Spatio-Temporal Intervention in Inter-personal Remote Physical Interactions on Playing Air Hockey." ACM SIGGRAPH 2021 Emerging Technologies, ACM, 2021.

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Tail-like Balancer

A reduced balance ability can lead to falls and critical injuries. To prevent falls, humans use reaction forces and torques generated by swinging their arms. In animals, we can find that a similar strategy is taken using tails. Inspired by these strategies, we propose an approach that utilizes a robotic appendage as a human balance supporter without assistance from environmental contact. As a proof of concept, we developed a wearable robotic appendage that has one actuated degree of freedom and rotates around the sagittal axis of the wearer. To validate the feasibility of our proposed approach, we conducted an evaluation experiment with human subjects. Controlling the robotic appendage we developed improved the subjects' balance ability and enabled the subject to withstand up to 22.8% larger impulse disturbances on average than in the fixed appendage condition.

publication:

• Azumi Maekawa, Kei kawamura, and Masahiko Inami. "Dynamic Assistance for Human Balancing with Inertia of a Wearable Robotic Appendage." In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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The Tight Game

Physical assistance can alleviate individual differences of abilities between players to create well-balanced inter-personal physical games. However, ‘explicit’ intervention can ruin the players’ sense of agency, and cause a loss of engagements in both the player and audience. We propose an implicit physical intervention system ”The Tight Game” for ‘Tug of War’ a one-dimensional physical game. Our system includes four force sensors connected to the rope and two hidden high torque motors, which provide realtime physical assistance. We designed the implicit physical assistance by leveraging human recognition of the external forces during physical actions. In The Tight Game, a pair of players engage in a tug of war, and believe that they are participating in a well balanced, tight game. In reality, however, an external system or person mediates the game, performing physical interventions without the players noticing.

publication:

• Azumi Maekawa, Shunichi Kasahara, Hiroto Saito, Daisuke Uriu, Ganesh Gowrishankar, and Masahiko Inami. "The Tight Game: Implicit Force Intervention in Inter-personal Physical Interactions on Playing Tug of War." ACM SIGGRAPH 2019 Emerging Technologies, ACM, 2020.

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PickHits

Experiences of hitting targets cause a great feeling. We propose a system for generating this experience computationally. This system consists of external tracking cameras and a handheld device for holding and releasing a thrown object. As a proof-of-concept system, we developed the system based on two key elements: low-latency release device and constant model-based prediction. During the user’s throwing motion, the ballistic trajectory of the thrown object is predicted in real time, and when the trajectory coincides with the desired one, the object is released. We found that we can generate a computational hitting experience within a limited range space.

publication:

• Azumi Maekawa, Seito Matsubara, Sohei Wakisaka, Daisuke Uriu, Atsushi Hiyama, and Masahiko Inami. "Dynamic Motor Skill Synthesis with Human-Machine Mutual Actuation." In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1-12.

• Azumi Maekawa, Seito Matsubara, Atsushi Hiyama, and Masahiko Inami. "PickHits: Hitting Experience Generation with Throwing Motion via a Handheld Mechanical Device." ACM SIGGRAPH 2019 Emerging Technologies. ACM, 2019.

credit:

Azumi Maekawa, Seito Matsubara

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Stand

The hardware design of the robots usually reflects its purpose. For example, leg for walking, arm for reaching, hand for grasping, etc. The function of mechanical systems are explicitly defined by designers and the simple shape consisting of straight lines or circular arcs is reasonable for its clarified function. On the other hand, our real environment is full of diverse shapes. The complex shape has been formed by various factors, biological growth, aging, weathering and so on. Utilizing diverse objects to create robots, we might be able to see behaviors and motions we’ve never seen. We aim to find unpredictable motions we could not discover with simple shapes. In this work, as a primitive function of the robot, we focus on stand-up behavior. For the materials that bricolage the robot, we select tree branches as objects with diverse shapes. The robots' poses are generated aiming to maximize the height of the bodies. Robots with diverse body shapes change their pose by repeating trial and error in real time. Through the process of learning, this work portrays new functions and meanings given to commonplace objects.

exhibition:

• Self Motto Satellite 2018 Autumn, knowledgscape

  KANA KAWANISHI GALLERY, Tokyo, Japan, 2018

credit:

Azumi Maekawa

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Arial-Biped

There has been a desire to create robots that are capable of life-like motions and behaviors since ancient times. As a life-like motion, we focus on the bipedal walking, which is one of the key features of a legged robot. Movement of the legged robot is highly restricted by gravity. When its body shape is defined, the possible walking gait is almost determined accordingly. Therefore, it is difficult to realize arbitrary body design and dynamic walking motion with light steps like living things in a legged robot. Aerial-Biped is a prototype for exploring a new experience with a physical biped robot. In this work, using a quadrotor, we aim to separate the body shape design and motion design. By releasing the biped robot from gravity, it can relax the limitation of the robot's physical motion. The motion of Aerial-Biped is created in real time according to the movement of the quadrotor by the motion generator learned using deep reinforcement learning. We can observe various gaits emerge based on the successively changing quadrotor's movements.

publication:

• Azumi Maekawa, Ryuma Niiyama, and Shunji Yamanaka. "Pseudo-Locomotion Design with a Quadrotor-Assisted Biped Robot." In 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 2462-2466. IEEE, 2018.
• Azumi Maekawa, Ryuma Niiyama, and Shunji Yamanaka. "Aerial-biped: a new physical expression by the biped robot using a quadrotor." ACM SIGGRAPH 2018 Emerging Technologies. ACM, 2018.

exhibition:

• Ars Electronica, "Out of the Box. The Midlife Crisis of the Digital Revolution"

  PostCity, Linz, Austria, 2019

• Parametric Move

  UTokyo-IIS Prototyping & Design Laboratory, Tokyo, Japan, 2018

media:

• IEEE Spectrum, 13 Aug, 2018
• Reuters, 2 Oct, 2018
• ASCII, 17 Jul, 2018
• designboom, 14 Aug, 2018
• TechCrunch, 14 Aug, 2018

credit:

Azumi Maekawa, Shunji Yamanaka

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