Yusuke Tamura

An efficient improved artificial potential field based regression search method for robot path planning

Path planning field for autonomous mobile robot is an optimization problem that involves computing a collision-free path between initial location and goal location. In this paper, we present an improved artificial potential field based regression search (Improved APF-based RS) method which can obtain a global sub-optimal/optimal path efficiently without local minima and oscillations in complete known environment information. We redefine potential functions to eliminate non-reachable and local minima problems, and utilize virtual local target for robot to escape oscillations. Due to the planned path by improved APF is not the shortest/approximate shortest trajectory, we develop a regression search (RS) method to optimize the planned path. The optimization path is calculated by connecting the sequential points which produced by improved APF. Amount of simulations demonstrate that the improved APF method very easily escape from local minima and oscillatory movements. Moreover, the simulation results confirm that our proposed path planning approach could always calculate a more global optimal/near-optimal, collision-free and safety path to its destination compare with general APF. That proves our improved APF-based RS method very feasibility and efficiency to solve path planning which is a NP-hard problem for autonomous mobile robot.

Effective improved artificial potential field-based regression search method for autonomous mobile robot path planning

This paper presents an effective improved artificial potential field-based regression search (improved APF-based RS) method that can obtain a better and shorter path efficiently without local minima and oscillations in an environment including known, partially known or unknown, static, and dynamic environments. We redefine potential functions to eliminate oscillations and local minima problems, and use improved wall-following methods for the robots to escape non-reachable target problems. Meanwhile, we develop a regression search method to optimise the planned path. The optimisation path is calculated by connecting the sequential points produced by improved APF. The simulations demonstrate that the improved APF method easily escapes from local minima, oscillations, and non-reachable target problems. Moreover, the simulation results confirm that our proposed path planning approach can calculate a shorter or more nearly optimal than the general APF can. Results prove our improved APF-based RS method’s feasi...

Development of pedestrian behavior model taking account of intention

In order for robots to safely move in human-robot coexisting environment, they must be able to predict their surrounding peoples behavior. In this study, a pedestrian behavior model that produces humanlike behavior was developed. The model takes into account the pedestrians intention. Based on the intention, the model pedestrian sets its subgoal and moves toward the subgoal according to virtual forces affected by other pedestrian and environment. The proposed model was verified through pedestrian observation experiments.

Analysis of manipulating other's attention for smooth interaction between human and robot

Understanding and predicting humans behavior by a robot is necessary for smooth interaction with humans. Humans often achieve them by guidance of others behavior, especially controlling its attention. Magicians can effectively manipulate spectators attention. In this study, we hypothesized that the relationship between magicians gaze and hands plays an important role for controlling spectators attention. To test the hypothesis, we carried out an experiment to measure gaze points of spectators who were watching magic videos and analyzed the result of the experiment. As a result, we obtained the result that when the magicians gaze coincided with his hands that were manipulating objects, the degree of attention drawing was higher than otherwise.

Visual attention model for manipulating human attention by a robot

For smooth interaction between human and robot, the robot should have an ability to manipulate human attention and behaviors. In this study, we developed a visual attention model for manipulating human attention by a robot. The model consists of two modules, such as the saliency map generation module and manipulation map generation module. The saliency map describes the bottom-up effect of visual stimuli on human attention and the manipulation map describes the top-down effect of face, hands and gaze. In order to evaluate the proposed attention model, we measured human gaze points during watching a magic video, and applied the attention model to the video. Based on the result of this experiment, the proposed attention model can better explain human visual attention than the original saliency map.

Modeling of human attention based on analysis of magic

In this study, we developed a human attention model for smooth human-robot interaction. The model consists of the saliency map generation module and manipulation map generation module. The manipulation map describes top-down factors, such as human face, hands and gaze in the input image. To evaluate the proposed model, we applied the model to a magic video, and measured human gaze points during watching the video. Based on the experimental results, the proposed model can better explain human attention than the saliency map. Categories and Subject Descriptors I.2.9 [Artificial Intelligence]: Robotics General Terms Human Factors

Activeness Improves Cognitive Performance in Human-Machine Interaction

∗1Faculty of Science and Engineering, Chuo University 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan E-mail: tamura@mech.chuo-u.ac.jp ∗2Recruit Marketing Partners, Co., Ltd. 1-9-2 Marunouchi, Chiyoda-ku, Tokyo 100-6640, Japan ∗3Research Organization of Science and Technology, Ritsumeikan University 1-1-1 Nojihigashi, Kusatsu-shi, Shiga 525-8577, Japan ∗4Department of Neuropsychiatry, Keio University School of Medicine 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan ∗5Graduate School of Engineering, The University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Modelling Behaviour Patterns of Pedestrians for Mobile Robot Trajectory Generation

Robots are expected to be operated in environments where they coexist with humans, such as shopping malls and offices. Both the safety and efficiency of a robot are necessary in such environments. To achieve this, pedestrian behaviour should be accurately predicted. However, the behaviour is uncertain and cannot be easily predicted. This paper proposes a probabilistic method of determining pedestrian trajectory based on an estimation of pedestrian behaviour patterns. The proposed method focuses on the specific behaviour of pedestrians around the robot. The proposed model classifies the behaviours of pedestrians into definite patterns. The behaviour patterns, distribution of the positions of the pedestrians, and the direction of each behaviour pattern are determined by learning through observation. The behaviour pattern of a pedestrian can be estimated correctly by a likelihood calculation. A robot decides to move with an emphasis on either safety or efficiency depending on the result of the pattern estimation. If the pedestrian trajectory follows a known behaviour pattern, the robot would move with an emphasis on efficiency because the pedestrian trajectory can be predicted. Otherwise, the robot would move with an emphasis on safety because the behaviour of the pedestrian cannot be predicted. Experimental results show that robots can move efficiently and safely when passing by a pedestrian by applying the proposed method.

Effect of Mediolateral Knee Displacement on Ligaments and Muscles around Knee Joint: Quantitative Analysis with Three-Dimensional Musculoskeletal Ligament Knee Model

Knee osteoarthritis (OA) becomes a major public issue, but a strategy to prevent the disease has not established yet due to lack of an accurate method to measure an internal motion of the knee of individual patients. Therefore mechanical engineering model and a standard of evaluation of the disease is needed to improve the situation. Currently, there are a few studies to develop the model including allowance of joint movement and ligaments. Thus this study shows the model accuracy by forward dynamics and discusses the result of inverse dynamics of various gait patterns. As a result, it can be confirmed that ligaments are more effective than muscles around knee joint with our various models. In addition we propose the important factor of knee OA from gait pattern and models.

Moving task allocation and reallocation method based on body expansion behaviour for distributed multi-robot coordination

The inconvenience and cost of utilising existing task assignment approaches to resolve dynamical mobile task allocation. For such new domain, we first propose a method, called dynamical-sequential task allocation and reallocation, by implementing multi-round negotiation and body expansion behaviour. Every former half time step, robots negotiate sequentially and select tasks to perform, and declare the information to other robots. When all robots have finished first time selection, then the remaining unselected robots choose the remaining unassigned tasks again sequentially at the latter half time step. We set two distance thresholds for robot decision-making to apply body expansion behaviour. The advantages of our methodology are demonstrated by comparison with existing algorithms, simulation results demonstrate that the efficiency for whole system to accomplish given tasks is improved by utilising our approach. Moreover, it is more conducive to reduce the numerous computational time and communication compared with existing investigated task assignment methods.