Mitsuhiro Kamezaki

To smoothly and efficiently enable autonomous mobile robots to move in human crowd environments, path planning based on human movement-prediction, reactive movement toward human movement, and active motion-inducing physical interaction to avoid getting stuck are required. In this study, we developed a reactive, proactive, and inducible proximal crowd navigation (PCN) method that is based on a newly developed inducible social force model ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/Ma

Human-aware navigation is an essential requirement for autonomous robots in human-coexisting environments. The goal of conventional navigation is to find a path for a robot to pass through safely and efficiently without colliding with human. Note that if such a path cannot be found, the robot stops until a path is clear. Thus, such collision-avoidance based passive navigation does not work in a congested or narrow space. To avoid this freezing problem, the robot should induce humans to make a sp

The aim of this study is to provide a machine operator with enhanced visibility and more adaptive visual information suited to the work situation, particularly advanced unmanned construction. Toward that end, we propose a method for autonomously controlling multiple environmental cameras. Situations in which the yaw, pitch, and zoom of cameras should be controlled are analyzed. Additionally, we define imaging objects, including the machine, manipulators, and end points; and imaging modes, includ

We developed a four-arm four-crawler advanced disaster response robot called OCTOPUS. Disaster response robots are expected to be capable of both mobility, e.g., entering narrow spaces over very rough unstable ground, and workability, e.g., conducting complex debris-demolition work. However, conventional disaster response robots are specialized in either mobility or workability. Moreover, strategies to independently enhance the capability of crawlers for mobility and arms for workability will in

Intelligent functions that can autonomously identify the current work states and also provide informational or operational support to their operators are inevitably required for double-front construction machinery (DFCM), which has been developed for complicated tasks. In this study, which focuses on DFCM, we address the need for a new conceptual design of an operator support system. In particular, a state identification method strongly requires high reliability and robustness to address the com

Advanced operated-work machines, which have been designed for complicated tasks and which have complicated operating systems, requires intelligent systems that can provide the quantitative work analysis needed to determine effective work procedures and that can provide operational and cognitive support for operators. Construction work environments are extremely complicated, however, and this makes state identification, which is a key technology for an intelligent system, difficult. We therefore

This paper reports a newly developed hydraulic dual robotic arm system to create and evaluate intelligent systems, which support complicated machine operations, for advanced construction machinery. This kind of machine system (test-bed) requires functions to quantify its dynamic characteristics and operational difficulty (influential factors). In particular, construction manipulator nonlinearly changes its dynamics depending on various internal and external factors. To quantify such influential

This paper reports a newly developed simulator for operation skill training in Double-Front Construction Machinery (DFCM) that allows novices to virtually experience tough operations repeatedly using DFCM under various conditions, including dangerous congestion. First, we selected several situations targeted where the DFCM needs to be used to provide a high level of operation skills: sorted dismantling for recycling and reusing resources, rescue and recovery work in disaster areas, and building

&lt;div class=""abs_img""&gt;&lt;img src=""[disp_template_path]/JRM/abst-image/00260004/11.jpg"" width=""300"" /&gt;Virtual reality simulator&lt;/span&gt;&lt;/div&gt; A virtual reality (VR) simulator is developed to aid in advancing teleoperated construction machines for disaster response work. VR simulators, which can measure arbitrary data, allow the operator to reproduce desired situations repeatedly, and change the machine and environmental configurations more easily than is possible in real

Path planning in dynamic environments is still a challenging issue with autonomous mobile robots. Current methods lack adaptability to various passing scenarios, a variety of passing trajectories including an acceleration path, or immediacy in planning time, which require human-aware navigation. In this study, we propose Dynamic Waypoint Navigation (DWN), which is a model-based adaptive real-time trajectory planning method. DWN first predicts human-robot path interference and the time and positi

Abstract Due to functional limitations in certain situations, the driver receives a request to intervene from automated vehicles operating level 3. Unscheduled intervention of control authority would lead to insufficient situational awareness, then this will make dangerous situations. The purpose of this study is thus to propose tactical-level input (TLI) method with a multimodal driver-vehicle interface (DVI) for the human-centered intervention. The proposed DVI system includes touchscreen, han

This paper proposes a practical scheme for measuring the mass of an object grasped by the end-effector of a large-scale hydraulic manipulator. Such a measurement system requires high accuracy and robustness considering the nonlinearity and uncertainty in hydraulic pressure-based force measurement during rigorous outdoor work. It is thus difficult to precisely model system behaviors and completely remove error force components (white-box modeling) under such conditions, so our scheme adopts a les

The state identification framework we propose supports complex construction machinery operations using a dual arm. Such support requires compatibility with different types of support and commonality among various operator skill levels. Our framework is organized into (i) real-time task phase identification defined using joint load applied based on environment constraints and (ii) time-series attentional condition identification defined as an internal work-state condition classified by the operat

Collaborative robots that operate safely close to workers without fences have attracted attention, but few examples of such human-robot collaboration (HRC) have been seen in factories. The main reason is the difficulty in balancing safety and productivity. Current fenceless HRC systems stop the robot when a human enters the collaborative workspace ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CC</i> ) where both human and robot can work to en