Kazuyuki Kon

Marine heterogeneous multirobot systems at the great Eastern Japan Tsunami recovery

This field report describes two deployments of heterogeneous unmanned marine vehicle teams at the 2011 Great Eastern Japan Earthquake response and recovery by the Center for Robot-Assisted Search and Rescue (USA) in collaboration with the International Rescue System Institute (Japan). Four remotely operated underwater vehicles (ROVs) were fielded in Minamisanriku and Rikuzentakata from April 18 to 24, 2011, for port clearing and victim recovery missions using sonar and video. The ROVs were used for multirobot operations only 46% of the time due to logistics. The teleoperated ROVs functioned as a dependent team 86% of the time to avoid sensor interference or collisions. The deployment successfully reopened the Minamisanriku New Port area and searched areas prohibited to divers in Rikuzentakata. The IRS-CRASAR team planned to return from October 18 to 28, 2011, with an unmanned aerial vehicle (UAV), an autonomous underwater vehicle (AUV), and an ROV to conduct debris mapping for environmental remediation missions. The intent was to investigate an interdependent strategy by which the UAV and AUV would rapidly conduct low-resolution scans identifying areas of interest for further investigation by the ROV. The UAV and AUV could not be used; however, the ROV was able to cover 80,000 m2 in 6 h, finding submerged wreckage and pollutants in areas previously marked clear by divers. The field work (i) showed that the actual and planned multirobot system configurations did not fall neatly into traditional taxonomies, (ii) identified a new measure, namely perceptual confidence, and (iii) posed five open research questions for multirobot systems operating in littoral regions.

Model Predictive Formation Control Using Branch-and-Bound Compatible With Collision Avoidance Problems

This paper presents a model predictive control (MPC) approach for multivehicle formation taking into account collision avoidance and velocity limitation with reduced computational burden. The first part of the paper constructs a formation control law using feedback linearization with MPC in order to reduce the optimal control problem to a mixed-integer quadratic programming problem for a group of unicycles. The second part constructs a new branch-and-bound (B& B) -based algorithm for collision-avoidance problems. Numerical examples and experiments show that the proposed method significantly reduces computation time.

Distributed Model Predictive Control for Multi-Vehicle Formation with Collision Avoidance Constraints

This paper presents a distributed model predictive control (MPC) method for unicycles information with collision avoidance constraints. The proposed method first stabilizes the system by using a feedback linearization, and then a collision avoidance method based on MPC is applied to the linearized system. One of the features of the proposed method is that each vehicle sequentially solves its optimal control problem at different time step. Unlike other MPC collision avoidance methods in which all vehicles solve optimal control problems at every time step, only one vehicle can solve its optimization problem at one time step. We derive a condition for the proposed method to ensure the feasibility of the optimization method and stability of the closed-loop system. The effectiveness of the method is also investigated by experiments.

Use of remotely operated marine vehicles at Minamisanriku and Rikuzentakata Japan for disaster recovery

Three underwater remotely operated vehicles (ROVs) were used over a five day period to inspect critical infrastructure and to assist with victim search and recovery at six sites in the Iwate Prefecture following the Tohoku Earthquake and Tsunami. Unmanned marine vehicles have been used since 2004 for disaster recovery operations but in limited applications, in single areas, and in short deployment durations. The joint IRS-CRASAR deployment matched robots for missions specified by civilian municipalities and the Japanese Coast Guard. The ROVs successfully allowed a fishing port to be re-opened and searched for victims trapped underwater in five different locations in varying areas (marinas, bridge debris, and waterfront residential areas) that could not be searched by manual divers. From a scientific perspective, the deployment provides a corpus of 15 hours of data of how rescue robots can be used. It illustrates that rescue robots are i) valuable for both economic and victim recovery, not just response, ii) that disaster robots need to be optimized for the unique missions and stakeholder needs, and iii) that human-robot interaction remains a challenge. This paper also identifies new areas for research: computer vision and cognitive engineering, cyber-physical systems, heterogeneous multi-robot coordination, human-robot interaction, simulation and geographical information systems.

Range-Sensor-Based Semiautonomous Whole-Body Collision Avoidance of a Snake Robot

This brief presents a control system for a snake robot based on range sensor data that semiautonomously aids the robot in avoiding collisions with obstacles. In the proposed system, an operator indicates the desired velocity of the first link of the robot using a joystick, and the joint input which accomplishes both the desired velocity of the first link and collision avoidance between subsequent links and obstacles is automatically calculated by the controller, which selects the links needed to be grounded and exploits redundancy. The controller uses real-time data from range sensors for obstacle positions. The experimental system, which has range sensors and the function generating environmental map using simultaneous localization and mapping, was developed with decreasing calculation cost, and experiments were performed to verify the effectiveness of the proposed system in unknown environments.

Control of a Group of Mobile Robots Based on Formation Abstraction and Decentralized Locational Optimization

In this paper, we propose a new method of controlling a group of mobile robots based on formation abstraction. The shape of a formation is represented by a deformable polygon, which is constructed by bending a rectangle, to go through narrow spaces without colliding with obstacles. If the trajectory of the front end point, as well as the width and the length of the formation, are given, the formation automatically reshapes itself to fit the area through which the front part of the group has already safely passed. Furthermore, the robots continuously try to optimize their positions to decrease the risk of collisions by integrating a decentralized locational optimization algorithm into the formation control. We show that the objective function, taking into account the distance between robots, does not decrease for fixed and nonconvex polygonal formation shapes if the zero-order hold control is applied for a sufficiently short sampling period. We also analyze the influence of the decentralized locational optimization algorithm on the objective function in the case of variable formations. The effectiveness of the proposed method is demonstrated in both simulations and real robot experiments.

Motion planning of an autonomous mobile robot considering regions with velocity constraint

Recently various autonomous mobile robots are developed for practical use. For coexistence with the robots and human in the real environment, the consideration of safety is very important. We should consider a region with a limitation of a maximum velocity of a mobile robot for the safety. In this paper, we propose path planning and trajectory generation methods for a mobile robot which moves in the environment with predetermined velocity constraints. In order to demonstrate the validity of the proposed methods, numerical simulations and experiments have been carried out.

Utilization of Robot Systems in Disaster Sites of the Great Eastern Japan Earthquake

In this paper, we report our activities in the real disaster areas damaged by the Great Eastern Japan Earthquake. From March 18–21, 2011, we tried to apply a ground rescue robot to the real disaster sites at Aomori Prefecture and Iwate Prefecture. On March 18, we carried out inspection mission in a damaged gymnasium. From March 19–21, we went to other sites to identify possibility of usage of robots, and we found the potential needs for not only ground robots but also underwater robots. Then, after the first activity we established a joint United States-Japanese team for underwater search. From April 19–23, 2011 the joint team brought four ROVs to Miyagi Prefecture for port inspection and to Iwate Prefecture for searching for submerged bodies. The joint team returned to Miyagi Prefecture October 22–26 with an AUV and two ROVs for cooperative debris mapping needed to assist with resuming fishing. Based on these experiences, we discuss the effectiveness and problems of applying the rescue robot in the real disaster sites.

Transformation Control to an Inverted Pendulum for a Mobile Robot With Wheel-Arms Using Partial Linearization and Polytopic Model Set

This paper presents a shape transformation control method of a mobile robot with wheel-arms. The proposed method aims at transformation from a four-wheeled mode for high-speed mobility to an inverted pendulum mode, which has advantages of high viewing position and small turning radius. The transformation starts with lifting up the wheel-arms to raise the center of gravity of the whole robot including the main body and arms. From such initial states, the body is lifted up and controlled to the target angle by partial linearization, while returning the arms to the initial angle. Then, the robot position is controlled by manipulating the target body angle. Unlike existing methods, we take into account the effects of the body angular velocity and the tracking error of the body angle by constructing a model set, which is composed of a single nominal model and its polytopic uncertainty for the system matrices. In order to derive the model set, we assume that the target body angle is constrained to a prescribed range. Therefore, the target body angle is manipulated using a model predictive control method, such that the closed-loop system is asymptotically stabilized, while the given constraint is satisfied, for all systems in the model set. The effectiveness of the proposed method is demonstrated in both simulations and real robot experiments.

Path planning for an autonomous mobile robot considering a region with a velocity constraint in a real environment

Recently, many research projects and competitions have attempted to find an autonomous mobile robot that can drive in the real world. In this article, we consider a path-planning method for an autonomous mobile robot that would be safe in a real environment. In such a case, it is very important for the robot to be able to identify its own position and orientation in real time. Therefore, we applied a localization method based on a particle filter. Moreover, in order to improve the safety of such autonomous locomotion, we improved the path-planning algorithm and the generation of the trajectory so that it can consider a region with a limited maximum velocity. In order to demonstrate the validity of the proposed method, we participated in the Real World Robot Challenge 2010. The experimental results are given.