13 accepted papers
In open-ended task settings, the ability of a robot to execute diverse tasks accurately by following language instructions is critical. Methods based on traditional imitation learning typically depend on extensive expert demonstrations and often struggle to generalize in the case of unseen scenarios…
This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. For multi-robots to efficiently perform tasks, it is necessary to manage the precedence dependencies between tasks. Although multi-robot decentralized and
Mobile manipulators require coordinated control of navigation and manipulation to accomplish tasks. Typically, coordinated mobile manipulation behaviors involve base navigation to approach the goal followed by arm manipulation to reach the desired pose. The embodiment selection between the base and
In open-ended task settings, the ability of a robot to execute diverse tasks accurately by following language instructions is critical. Methods based on traditional imitation learning typically depend on extensive expert demonstrations and often struggle to generalize in the case of unseen scenarios
In this study, we propose a shared control method for teleoperated mobile robots using brain-machine interfaces (BMI). The control commands generated through BMI for robot operation face issues of low input frequency, discreteness, and uncertainty due to noise. To address these challenges, our metho…
This paper discusses the tele-operation system for multiple mobile manipulators. If a single person could freely tele-operate multiple mobile manipulators simultaneously, it would be a great step toward the goal of “avatar-symbiotic society” allowing people to live beyond the constraints of their bo…
With the advancements in the field of life sciences, there is an increasing demand for measuring cell characteristics. In this context, we developed a small microhand system that uses two end-effectors, such as chopsticks, to grasp and carry micro-objects. In addition, we succeeded in measuring the
Humans perceive continuous high-dimensional information by dividing it into significant segments such as words and units of motion. We believe that such unsupervised segmentation is also important for robots to learn topics such as language and motion. To this end, we previously proposed a hierarchi…
In this paper, we propose a method for motion learning aimed at the execution of autonomous household chores by service robots in real environments. For robots to act autonomously in a real environment, it is necessary to define the appropriate actions for the environment. However, it is difficult t…
In this paper, we propose a method for motion learning aimed at the execution of autonomous household chores by service robots in real environments. For robots to act autonomously in a real environment, it is necessary to define the appropriate actions for the environment. However, it is difficult t
Humans recognize perceived continuous information by dividing it into significant segments such as words and unit motions. We believe that such unsupervised segmentation is also an important ability that robots need to learn topics such as language and motions. Hence, in this paper, we propose a met…
One of the biggest challenges in intelligent robotics is to build robots that can learn to use language. To this end, we think that the practical long-term on-line concept/word learning algorithm for robots is a key issue to be addressed. In this paper, we develop an unsupervised on-line learning al…
We propose a method for a robot to form various concepts. The robot uses its embodiment to obtain visual, auditory, and haptic information by grasping, shaking, and observing objects. At the same time, a user teaches the robot object features through speech. From these kinds of information, the robo…