鈴木 智

森林域でのこれまでのレーザー計測は、データ取得後に解析までの時間的ギャップがあり、データ取得後すぐに結果を確認することができなかった。3次元データを容易に取得できるモバイルレーザーに注目し、データ取得後すぐにデータ解析できるようにアルゴリズムをまとめた。3次元データ取得には小型センサーであるAVIA（DJI社製）を用い、自己位置を推定しながら即座にデータ合成するSLAM技術を用いた。木の周りを歩きながら様々な角度からデータを収集し、データ合成を即時に行った。得られた3次元データを小型画面で様々な角度で表示させ、画面上をクリックすることで樹高などの計測を容易にできるようにした。人の手が届かない場所をレーザーによって計測できるようにし、さらにデータを画像上で表示、簡単にタップして計測できるようにしたことで、これまで不可能であった計測をオンタイムでできる仕組みを構築できた。オンタイム計測による新たなデータ収集方法を確立したことで、i-Treeなどの樹木評価システムと連動させると、計測できていなかった樹木をより正確にデータ収集できる。カーボンニュートラルを実現するために未測定の樹木データ収集を促進していきたい。

これまでの森林管理におけるドローンの使用は、森林上空から照射されるレーザーもしくは写真データからSfMで作成される3次元データを使用してきた。本研究では、森林内を飛行できるドローンを開発し、アクセス困難な森林内で材積推定に必要な幹を直接計測できるようにした。本研究ではドローンに3次元レーザーを搭載し、常時スキャンすることで、障害物回避と樹木計測を同時に行い、森林内で衝突回避しながら樹木の幹形状をオンタイムで解析できる手法を確立した。SLAM技術をレーザーと併用し、飛行中にレーザーデータを結合してマッピングを行った。現在のドローンではバッテリーで飛行できる時間はおおよそ30分程度であるため、限られた時間内で取得できるデータから広域の森林を推定するサンプリング手法を開発し、計測した幹データの一部から5%の誤差以内で森林全体を推定できるようにした。本研究により開発した手法で、これまでアクセス困難であった林内でデータが取得でき、衛星や航空機などの森林上空で取得されるデータでは確認困難であった森林内状況を、ドローンで面的にデータを入手することが可能となった。

Recently, in order to carry out tasks efficiently such as infrastructure inspection and goods transportation, operations using multi-rotor Unmanned Aerial Vehicles (UAVs) in formation flight are often considered. One of the main issues in motion planning among multiple UAVs is collision avoidance. Model Predictive Control (MPC) is characterized by its ability to consider collision avoidance in the framework of constrained optimization. For this reason, there have been many studies on collision avoidance using MPC, but few studies take into account the uncertainty that occurs in real environments. On the other hand, Chance constrained MPC (CCMPC) is considered to be more robust in collision avoidance due to the consideration of uncertainty. However, the structure of the collision probability constraint equation to be introduced into the evaluation function of MPC has not been sufficiently studied. In this study, the structure of equations for incorporating probability constraints into the evaluation function is examined. Moreover, by quantitatively comparing the equations with the same structure with deterministic constraints introduced into the evaluation function, the difference in collision avoidance is clarified.

This chapter contains from Sects. 3.1 to 3.5. Section 3.1 describes firstly the definition of drones and recent trends. The important functions of the search and rescue flying robot are also generally described. And, Sect. 3.1 consists of an overview of R&D technologies of flying robot in Tough Robotics Challenge and a technical and general discussion about a future prospective of flying robot including the real disaster survey and technical issues. Namely, drones or unmanned aerial vehicles (UAVs) should be going to real and bio-inspired flying robot.

In this study, we aim at realizing the adaptive control system that enables the multi-rotor helicopter to fly autonomously without the tuning by human operator. This paper presents the design of the inner loop feedback control of multi-rotor helicopter based on adaptive PID control. The controller is designed by using the theory of simple adaptive control (SAC) method. Numerical simulation and flight experiment are carried out to verify the efficiency of proposed feedback control. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.

In this paper, collision-free guidance control of multiple small aerial robots is designed. Collision avoidance should be considered in the operation of a fleet of aerial robots. A guidance control system using a distributed model predictive control (DMPC) is proposed to realize the collision avoidance. A constraint of the relative position vector between each robot is considered in the design for efficient avoidance. Small multi-rotor helicopter is considered as controlled object, and the guidance control system is designed by using the translational model of the helicopter. The robots exchange information about current state and optimal input sequence each other for calculating the predictive trajectory of others. Based on the calculated trajectories, each helicopter solves its local optimization problem. Here, sharing the velocity information is difficult because calculation processing capability of the small sensor and communication capability among the robots are strictly restricted. Therefore, a dynamic compensator for velocity compensation is introduced. By introducing the dynamic compensator, collision avoidance using only exchange on the position and the input sequence information is accomplished without exchanging velocity information. The effectiveness of the proposed control system is verified by numerical simulations and flight experiment.

Clothes are very important for daily life. We always wash, dry, and fold them for maintenance of clothes. Washing and drying were already automated. However, folding isn't automated. Automation of folding clothes is expected for not only industry, but also home use. Unfortunately, folding system for home use is not perfect yet. A folding system is implement with normal table and small mobile robots which developed in this study. There are clothes and the camera on the table, because it can be provided only narrow space for this system while use in homes. In this paper, we proposed folding motion with edge of table and automated the folding system considering limit of work space.

In this study, novel robust navigation system for aerial robot in GPS and GPS- denied environments is proposed. Generally, the aerial robot uses position and velocity information from Global Positioning System (GPS) for guidance and control. However, GPS could not be used in several environments, for example, GPS has huge error near buildings and trees, indoor, and so on. In such GPS-denied environment, Laser Detection and Ranging (LIDER) sensor based navigation system have generally been used. However, LIDER sensor also has an weakness, and it could not be used in the open outdoor environment where GPS could be used. Therefore, it is desired to develop the integrated navigation system which is seamlessly applied to GPS and GPS-denied environments. In this paper, the integrated navigation system for aerial robot using GPS and LIDER is developed. The navigation system is designed based on Extended Kalman Filter, and the effectiveness of the developed system is verified by numerical simulation and experiment.