A novel path planning algorithm based on twofold interpolations

Path planning is one of the key technologies for unmanned surface vehicle (USV) to realize intelligent navigation. However, most path planning algorithms only consider the shortest path length and ignore other constraints during the navigation, which may generate a path that is not practically optimal in the view of safety and angular constraints. To solve this problem, an optimal path planning algorithm for USV based on fast marching method (FMM) is proposed in this paper. Firstly, a arrival time potential field with the only minimum point is generated by executing FMM on the initial binary map, which is used as a basic model for path planning. Secondly, to modeling the safety and heading angle constraints of the vehicle, the saturated safety map based on SFMS and the virtual obstacles formed by USV's turning ability are introduced and applied respectively. Thirdly, the gradient descent method is used on the improved potential field to search out an optimal path that can well meet the actual constrains of USV. The effectiveness and rationality of the algorithm are then verified by simulations.

Biped gait generation via iterative learning control including discrete state transitions

PurposeThe purpose of this paper is to put forward a rolling assistant robot with two rolling modes, and the multi-mode rolling motion strategy with path planning algorithm, which is suitable to this multi-mode mobile robot, is proposed based on chessboard-shaped grid division (CGD).Design/methodology/approachBased on the kinematic analysis and motion properties of the mobile parallel robot, the motion strategy based on CGD path planning algorithm of a mobile robot with two rolling modes moving to a target position is divided into two parts, which are local self-motion planning and global path planning. In the first part, the mobile parallel robot can move by switching and combining the two rolling modes; and in the second part, the specific algorithm of the global path planning is proposed according to the CGD of the moving ground.FindingsThe assistant robot, which is a novel 4-RSR mobile parallel robot (where R denotes a revolute joint and S denotes a spherical joint) integrating operation and rolling locomotion (Watt linkage rolling mode and 6R linkage rolling mode), can work as a moving spotlight or worktable. A series of simulation and prototype experiment results are presented to verify the CGD path planning strategy of the robot, and the performance of the path planning experiments in simulations and practices shows the validation of the path planning analysis.Originality/valueThe work presented in this paper is a further exploration to apply parallel mechanisms with two rolling modes to the field of assistant rolling robots by proposing the CGD path planning strategy. It is also a new attempt to use the specific path planning algorithm in the field of mobile robots for operating tasks.

One of the technologies in the industrial world that utilizes robots is the delivery of goods in warehouses, especially in the goods distribution process. This is very useful, especially in terms of resource efficiency and reducing human error. The existing system in this process usually uses the line follower concept on the robot's path with a camera sensor to determine the destination location. If the line and destination are not detected by the sensor or camera, the robot's navigation system will experience an error. it can happen if the sensor is dirty or the track is faded. The aim of this research is to develop a robot navigation system for efficient goods delivery in warehouses by integrating odometry and Dijkstra's algorithm for path planning. Holonomic robot is a robot that moves freely without changing direction to produce motion with high mobility. Dijkstra's algorithm is added to the holonomic robot to obtain the fastest trajectory. by calculating the distance of the node that has not been passed from the initial position, if in the calculation the algorithm finds a shorter distance it will be stored as a new route replacing the previously recorded route. the distance traversed by the djikstra algorithm is 780 mm while a distance of 1100 mm obtains the other routes. The time for using the Djikstra method is proven to be 5.3 seconds faster than the track without the Djikstra method with the same speed. Uneven track terrain can result in a shift in the robot's position so that it can affect the travel data. The conclusion is that odometry and Dijkstra's algorithm as a planning system and finding the shortest path are very efficient for warehouse robots to deliver goods than ordinary line followers without Dijkstra, both in terms of distance and travel time.

This paper analyzes the diagnosability of faults in a plant modelled by finite state automaton tables (FATs). The state-space is partitioned by choosing a set of boundaries for each state variable. Given the set of ordinary differential equations of the plant, it is possible to generate a finite-state automaton table (FAT) representation of the plant that describes possible discrete state transitions under normal and under fault conditions. The FAT serves as input to a fault detection and isolation algorithm. In this paper, we extend our earlier work to propose a definition of fault diagnosability and analyze the nondiagnosable circumstances. The proposition is illustrated with an example.

This paper deals with a kind of hybrid system that is obtained by making cellular automata infinitely small. Each point on a continuous space is defined as a state transition system with a finite number of discrete states that changes its state according to its previous state and the states of its neighbors. Time is also defined as continuous, so that state transitions may propagate through the space continuously over time. Discrete state transitions can be made instantaneously, as in the case of ordinary hybrid systems. It turned out that even defining the global behaviors that satisfy local transition rules is not trivial. The framework that we propose here can be regarded as a framework for amorphous computing.KeywordsState TransitionHybrid SystemCellular AutomatonInference RuleTransition RuleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Fuzzy discrete event systems (FDESs) have been introduced in recent years to model systems whose discrete states or discrete state transitions can be uncertain and are, hence, determined by a possibility degree. This paper develops an FDES framework for the control of sampled data systems that have to fulfill multiple objectives. The choice of a fuzzy system representation is justified by the assumption of a controller realization that depends on various potentially imprecise sensor measurements. The proposed framework consists of three basic steps that are performed at each sampling instant. First, the current fuzzy state of the system is determined by a sensor evaluation. Second, the fuzzy state in the future sampling instant is predicted for all possible control actions of the system. Finally, an original multiobjective weighting strategy is proposed to determine the control action to be applied in the current sampling instant. The features of the proposed approach are demonstrated by a detailed mobile robot example, which includes a simulation study.

The dynamic behavior of a car can be modeled as a hybrid system involving continuous state changes and discrete state transitions. We show that the control of safe (collision free) lane change maneuvers in multi-lane traffic on highways can be described by finite state machines extended with continuous variables coming from the environment. We use standard theory for controller synthesis to derive the dynamic behavior of a lane-change controller. Thereby, we contrast the setting of interleaving semantics and synchronous concurrent semantics. We also consider the possibility of exchanging knowledge between neighboring cars in order to come up with the right decisions. Finally, we address compositional verification using an assumption-guarantee paradigm.

This paper describes a position estimation method of a wheeled mobile robot by integrating the informations in an odometric dead reckoning and a laser navigation system. The dead reckoning regularly gives the robot's position by the revolution counts of both side wheels. The laser navigation system succesively observes the bearing angles relative to the corner cube reflectors fixed in the robot's environment. The chi-squared hypothesis testing is applied to reliably identify the corner cubes. The identified angle measurements modify the robot's position calculated by the dead reckoning based on the Extended Kalman filtering. The plant model is introduced from the kinematic equation concerning the dead reckoning, which regards both the robot's position and the wheel's radius as the state variables and the encoder measurement as the input variable. The measurement model is built concerning the bearing to a corner cube reflector in environment observed by the scanned laser. The proposed method enables the robot to accurately estimate the position even under uncertainty of the wheel's radius and the robot's motion with slippage in the cluttered environment. The simulation and experimental results justify the proposed method.

Grid-based path finding is required in many video games and virtual worlds to move agents. With both map sizes and the number of agents increasing, it is important to develop path finding algorithms that are efficient in memory and time. In this work, we present an algorithm called DBA* that uses a database of pre-computed paths to reduce the time to solve search problems. When evaluated using benchmark maps from Dragon AgeTM, DBA* requires less memory and time for search, and performs less pre-computation than comparable real-time search algorithms. Further, its suboptimality is less than 3%, which is better than the PRA* implementation used in Dragon AgeTM.KeywordsVideo GameOptimal PathSector SizeRegion RepresentativePath MatrixThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Mobile Robot Vision Tracking System Using Dead Reckoning & Active Beacons

In this paper we analyze the existing defects of hierarchical and nonhierarchical path finding algorithm respectively in detail and present a hierarchical path finding algorithm based on the heuristic directing search approach which is used for promoting the nodes of lower level to higher level in the road network. The improved heuristic-hierarchical path finding algorithm was tested on road network of Xi'an city with a two-level hierarchy. The experimental results show that the heuristic based hierarchical path finding algorithm has been found to be over 25 times faster than the Dijkstra's algorithm and the ratio of the highest level road obtained by heuristic based hierarchical path finding algorithm is twice as much as the Dijkstra's algorithm. This means that the hierarchical path finding algorithm is suitable for the status of long-distance between origin and destination ( O- D). We also propose a novel yet simple path finding strategy based on a threshold, that is, if the distance of O- D is less than the threshold which was obtained by means of statistical analysis the nonhierarchical path finding algorithm will be used, otherwise we use hierarchical path finding algorithm to find a near-optimal or satisfactory path in city road network. The testing results of Xi'an city road network show that the roads which were found out using this new path finding strategy are easy to be adopted by drivers.

Accurate dynamic modeling and control parameters design of an industrial hybrid spray-painting robot

The National Achievement Center (Puspresnas) and the Ministry of Education and Culture of the Republic of Indonesia proudly present the Indonesian Ash Robot Contest (KRAI), a yearly student robotics competition where teams tackle ash-related challenges with their robot creations. At KRAI 2021, it was shown that many robots were controlled using joysticks and resulted in a lack of effectiveness in robotic motion. The use of a joystick makes the movement of the robot take longer. This is because the robot is controlled by humans and the robot has not been able to pinpoint the robot's location. Gyrodometry is a method to map the robot's position using a inner ear and compass of the machine. In this research, Gyrodometry is used to map the position based on the readings of the gyroscope sensor and rotary encoder so that the robot can move automatically. In this research, the KRAI hitter robot can map positions and move in an accurate direction and can move automatically and effectively so that it can save more time and can increase the possibility of strategy in the match. From the results of this study, it was found that without using gyrodometry the error of X reached 11.825 cm and Y reached 35.1325 cm and also the angle error reached 13.7 degrees. and by using gyrodometry error X reaches 4.25 cm and Y reaches 5.775 cm and angle error 2.01 degrees. From these results, it was found that using gyrodometry was better than without using gyrodometry. The addition of waypoints to the robot only produces an average error of 8.2 cm X and Y error of -7.8 cm and the angle error reaches 10.2 degrees.

A set of autonomous robots have to collaborate in order to accomplish a common task in a ring-topology where neither nodes nor edges are labeled. We present a unified approach to solve three important problems: the exclusive perpetual exploration, the exclusive perpetual search and the gathering problems. In the first problem, each robot aims at visiting each node infinitely often; in perpetual graph searching, the team of robots aims at clearing the whole network infinitely often; and in the gathering problem, all robots must eventually occupy the same node. We investigate these tasks in the Look-Compute-Move distributed computing model where the robots cannot communicate but can perceive the positions of other robots. Each robot is equipped with visibility sensors and motion actuators, and it operates in asynchronous cycles. In each cycle, a robot takes a snapshot of the current global configuration (Look), then, based on the perceived configuration, takes a decision to stay idle or to move to one of its adjacent nodes (Compute), and in the latter case it eventually moves to this neighbor (Move). Moreover, robots are endowed with very weak capabilities. Namely, they are anonymous, oblivious, uniform (execute the same algorithm) and have no common sense of orientation. In this setting, we devise algorithms that, starting from an exclusive rigid (i.e. a periodic and asymmetric) configuration, solve the three above problems in anonymous ring-topologies.