Manipulating a non-humanoid body using a mapping approach that translates human body activity into different structural movements enables users to perform tasks that are difficult with their innate bodies. However, a key challenge is how to design an effective mapping to control non-analogous body parts with the human body. To address this challenge, we designed an articulated virtual arm and investigated the effect of mapping methods on a user’s manipulation experience. Specifically, we developed an unbranched 12-joint virtual arm with an octopus-like appearance. Using this arm, we conducted a user study to compare the effects of several mapping methods with different arrangements on task performance and subjective evaluations of embodiment and user preference. As a result, we identified three important factors in mapping: “Visual and Configurational Similarity”, “Kinematics Suitability for the User”, and “Correspondence with Everyday Actions.” Based on these findings, we discuss a mapping design for non-humanoid body manipulation.

Technological advancement has opened up opportunities for new sports and physical activities. We introduce a concept called machine-mediated teaming, in which a human and a surrogate machine form a team to participate in physical sports games. To understand the experience of machine-mediated teaming and the guidelines for designing the system to achieve the concept, we built a case study system based on tug-of-war. Our system is a sports game played by two against two. One team consists of a player who actually pulls the rope and another player who participates in the physical game by controlling the machine’s actuators. We conducted user studies using this system to investigate the sport experience in this form and to reveal insights to inform future research on machine-mediated teaming. Based on the data obtained from the user studies, we clarified three perspectives, machine stamina, action space, and explicit feedback, that should be considered when designing future machine-mediated teaming systems. The research presented in this paper offers a first step towards exploring how humans and machines can coexist in highly dynamic physical interactions.

We propose a simple speech compression algorithm using subband division and subadaptive piecewise linear quantization for a voice-mail system. Voice mail is an audio equivalent of sending letters. The main differences are that computer networks deliver the mail and that electronic recording is used instead of letters. Although speech data are stored in a semiconductor memory device, its capacity and the available network capacity are limited. Therefore, it is necessary to compress the data as much as possible. However, there are two conditions to be satisfied. The first is that the reconstructed datum must be understood correctly. Second, we need to identify the sender. Signals with a rate of 64 kbit/s are compressed at a ratio of about 1/9 using the proposed subband division and subadaptive piecewise linear quantization.