Collision-free Coordination Research Articles

Robust Near-Optimal Coordination in Uncertain Multiagent Networks With Motion Constraints.

This article addresses the robust coordination problem for nonlinear uncertain second-order multiagent networks with motion constraints, including velocity saturation and collision avoidance. A single-critic neural network-based approximate dynamic programming approach and exact estimation of unknown dynamics are employed to learn online the optimal value function and controller. By incorporating avoidance penalties into tracking variable, constructing a novel value function, and designing of suitable learning algorithms, multiagent coordination and collision avoidance are achieved simultaneously. We show that the developed feedback-based coordination strategy guarantees uniformly ultimately bounded convergence of the closed-loop dynamical stability and all underlying motion constraints are always strictly obeyed. The effectiveness of the proposed collision-free coordination law is finally illustrated using numerical simulations.

Dual Arm Coordination with Coordination Diagram Based on Teleoperation Demonstration

Efficient and collision-free coordination of two robot arms is increasingly needed in various service-oriented robotic applications. This paper proposes a dual arm coordination algorithm to improve the efficiency of coordination by considering both robot’s actions and operating sequences of the tasks that need to use two arms to complete complex operations. Teleoperation demonstration is first performed to obtain the robot’s human-like motion trajectories, so as to reduce the probability of the collisions between the two arms. The coordination diagram in time domain is then designed to more clearly represent the situations of trajectory collisions and find the collision-free coordination action law. A Coordination Pair Generator (CPG) is designed to reorganize the operating sequences according to the characteristics of input trajectories and the action coordination. The effectiveness and efficiency of our method are verified on the simulation and physical experiments which execute the drug sorting task in nursing homes, respectively, on the ABB YuMi robot model and self-developed robot system. According to the experiment results, the operation time has been reduced by 9% and the collision area has been reduced by 7.5%.

Learning-based collision-free coordination for a team of uncertain quadrotor UAVs

This paper investigates the safe coordination problem for a team of quadrotor unmanned air vehicles (UAVs) in the presence of model uncertainties and polygonal obstacles. Firstly, collision avoidance potential functions (PFs) related with both positions and velocities are utilized to construct the basic and bounded controller for achieving collision-free coordination. Then, in order to enhance the tracking performance under model uncertainties, an complementary control is developed via approximate dynamic programming (ADP), where the unknown dynamics of UAVs are accurately estimated in finite-time. Through using stored data in learning-based ADP, the approximated error of the weights in critic neural network converges with finitely excited signal. The sufficient conditions of the closed-loop system stability and collision avoidance are derived. The performance of the learning-based coordination methodology is demonstrated via simulation results.

An Overview of Recent Advances in Coordinated Control of Multiple Autonomous Surface Vehicles

Autonomous surface vehicles (ASVs) are marine vessels capable of performing various marine operations without a crew in a variety of cluttered and hostile water/ocean environments. For complex missions, there are increasing needs for deploying a fleet of ASVs instead of a single one to complete difficult tasks. Cooperative operations with a fleet of ASVs offer great advantages with enhanced capability and efficacy. Despite various application potentials, coordinated motion control of ASVs pose great challenges due to the multiplicity of ASVs, complexity of intravehicle interactions and fleet formation with collision avoidance requirements, and scarcity of communication bandwidths in sea environments. Coordinated control of multiple ASVs has received considerable attention in the last decade. This article provides an overview of recent advances in coordinated control of multiple ASVs. First, some challenging issues and scenarios in motion control of ASVs are presented. Next, coordinated control architecture and methods of multiple ASVs are briefly discussed. Then, recent results on trajectory-guided, path-guided, and target-guided coordinated control of multiple ASVs are reviewed in detail. Finally, several theoretical and technical issues are suggested to direct future investigations including network-based coordination, event-triggered coordination, collision-free coordination, optimization-based coordination, data-driven coordination of ASVs, and task-region-oriented coordination of multiple ASVs and autonomous underwater vehicles.

Collective Behaviors of Mobile Robots Beyond the Nearest Neighbor Rules With Switching Topology.

This paper is concerned with the collective behaviors of robots beyond the nearest neighbor rules, i.e., dispersion and flocking, when robots interact with others by applying an acute angle test (AAT)-based interaction rule. Different from a conventional nearest neighbor rule or its variations, the AAT-based interaction rule allows interactions with some far-neighbors and excludes unnecessary nearest neighbors. The resulting dispersion and flocking hold the advantages of scalability, connectivity, robustness, and effective area coverage. For the dispersion, a spring-like controller is proposed to achieve collision-free coordination. With switching topology, a new fixed-time consensus-based energy function is developed to guarantee the system stability. An upper bound of settling time for energy consensus is obtained, and a uniform time interval is accordingly set so that energy distribution is conducted in a fair manner. For the flocking, based on a class of generalized potential functions taking nonsmooth switching into account, a new controller is proposed to ensure that the same velocity for all robots is eventually reached. A co-optimizing problem is further investigated to accomplish additional tasks, such as enhancing communication performance, while maintaining the collective behaviors of mobile robots. Simulation results are presented to show the effectiveness of the theoretical results.

Collision avoidance in next-generation fiber positioner robotic systems for large survey spectrographs

Some of the next generation massive spectroscopic survey projects, such as DESI and PFS, plan to use thousands of fiber positioner robots packed at a focal plane to quickly move in parallel the fiber-ends from the previous to the next target points. The most direct trajectories are prone to collision that could damage the robots and impact the survey operation. We thus present here a motion planning method based on a novel decentralized navigation function for collision-free coordination of fiber positioners. The navigation function takes into account the configuration of positioners as well as the actuator constraints. We provide details for the proof of convergence and collision avoidance. Decentralization results in linear complexity for the motion planning as well as dependency of motion duration with respect to the number of positioners. Therefore the coordination method is scalable for large-scale spectrograph robots. The short in-motion duration of positioner robots (~2.5 seconds using typical actuator constraints), will thus allow the time dedicated for observation to be maximized.

Decentralized Motion Coordination for a Formation of Rovers

In this paper, a decentralized formation control is proposed which enables collision free coordination and navigation of agents. We present a simple method to define the formation of multi-agents and individual identities (IDs) of agents. Two decentralized coordination and navigation techniques are proposed for the formation of rovers. Agents decide their own behaviors onboard depending upon the motion initiative of the master agent of the formation. In these approaches, any agent can estimate behavior of other agents in the formation. These will reduce the dependency of individual agent on other agents while taking decisions. These approaches reduce the communication burden on the formation where only the master agent broadcasts its motion status per sampled time. Any front agent can act as a master agent without affecting the formation in case of fault in initial master agent. The main idea of this paper is to develop an adequate computational model under which agents in the formation will perform to coordinate among each other. Assignments of IDs to agents are very useful in real-time applications. These proposed schemes are suitable for obstacle avoidance in unknown environment as a whole formation. Agents are free from collision among each other during navigation. These schemes can be used for velocity as well as orientation alignment problems for a multi-agent rover network. These schemes are tested with extensive simulations and responses of agents show satisfactory performances to deal with different environmental conditions.

An elastic force based collision avoidance method and its application to motion coordination of multiple robots

A key contribution of robots to a manufacturing system is flexibility and automation. The robots can handle part batches of varying size and mix and can adapt to process variations and uncertainties in the working environment. This paper proposes a method for the collision-free motion coordination of multiple robots in a common working environment. The method uses an improved elastic force based method for collision avoidance. For the motion coordination of multiple robots, prioritisation-and-avoidance is used. Priority is assigned to each robot with a robot of lower priority avoiding the robots of higher priority. Without priority, every robot takes pains to avoid all the other robots. This degrades the overall performance of the coordinated motion. In addition, priority allows a robot with an urgent job to perform its job quicker. For collision avoidance, elastic force as well as potential field force is used. Compared with the method using only the potential field force, the robot can keep its configuration while avoiding other robots. Moreover, by adjusting the elastic force, task-consistent motion is possible. This method is tested by simulation and results in a smooth and adaptive coordination in an environment with different types of robots. Also the proposed method is compared with a method using the conventional elastic strip based method. The method can be used to coordinate the motion of multiple robots in a common working environment of a CIM system without interference.

Collision-free motion coordination of heterogeneous robots

This paper proposes a method to coordinate the motion of multiple heterogeneous robots on a network. The proposed method uses prioritization and avoidance. Priority is assigned to each robot; a robot with lower priority avoids the robots of higher priority. To avoid collision with other robots, elastic force and potential field force are used. Also, the method can be applied separately to the motion planning of a part of a robot from that of the other parts of the robot. This is useful for application to the robots of the type mobile manipulator or highly redundant robots. The method is tested by simulation, and it results in smooth and adaptive coordination in an environment with multiple heterogeneous robots.

Local collision avoidance of multiple robots using avoidability measure and relative distance

This paper presents a new method driving multiple robots to their goal position without collision. To consider the movement of the robots in a work area, we adopt the concept of avoidability measure. The avoidability measure figures the degree of how easily a robot can avoid other robots considering the velocity of the robots. To implement the concept to avoid collision among multiple robots, relative distance between the robots is proposed. The relative distance is a virtual distance between robots indicating the threat of collision between the robots. Based on the relative distance, the method calculates repulsive force against a robot from the other robots. Also, attractive force toward the goal position is calculated in terms of the relative distance. These repulsive force and attractive force are added to form the driving force for robot motion. The proposed method is simulated for several cases. The results show that the proposed method steers robots to open space anticipating the approach of other robots. In contrast, since the usual potential field method initiates avoidance motion later than the proposed method, it sometimes fails preventing collision or causes hasty motion to avoid other robots. The proposed method works as a local collision-free motion coordination method in conjunction with higher level of task planning and path planning method for multiple robots to do a collaborative job.

A deadlock-free algorithm for planning a collision-free coordinated motion for two mobile robots amidst unknown environments

This paper proposes a deadlock-free algorithm for planning a collision-free coordination for two mobile robots in an unknown environment using local information from their sensors. This algorithm achieves coordination planning by a two-level strategy. In the case where there is no risk of a collision, the robots move independently under the Bug2 algorithm proposed by Lumelsky. However, if a potential collision is expected, their motions are coordinated on the basis of a task-coordination space, which represents the position states of the robots on their paths. By controlling the motion of a point in the task-coordination space, any potential collision between the robots can be successfully avoided. The usefulness of this algorithm is discussed theoretically and shown by a simulation.

局所センサ情報を用いた未知環境における複数の移動ロボットの運動計画法

When multiple mobile robots are working in the same environment, it is necessary to plan such motions for the robots that they never collide each other. This paper proposes a useful algorithm for planning a collision-free coordination for two mobile robots in an unknown environment on the basis of local information from their sensors. This algorithm conquers the problem of coordination planning by a two-levels strategy. In the case that no collision between two robots is detected, the robots are independently guided by the motion planning algorithm proposed by V. Lumelsky. However, in the case that a potential collision is expected, their motions are coordinated to avoid the collision. To coordinate the robots, a two-dimensional task space (T-space) and a point automaton are introduced. By controlling the motion of the automaton in the T-space, any collision between the robots can be successfully aboided. Convergence of the proposed algorithm is proved, and its usefulness is shown by a simulation.

A new solid model HSM and its application to interference detection between moving objects

In order to realize collision-free coordination of multiple robots, it is crucial to model the robots in a computer adequately and to detect existence or nonexistence of an interference between them on the basis of data structure of the robot models. Motivated by this observation, this article proposes a new solid model named “Hierarchical Sphere Model” (HSM) for modeling moving objects (robots) and presents a feasible algorithm for checking an interference between them on the basis of HSM. HSM arranges region informations in a hierarchical tree structure whose nodes correspond to spherical regions. On the basis of hierarchy of HSM, the algorithm checks only intersections between HSMs' nodes which are close to each other, and hence it works efficiently even if the objects have complicated shape. Furthermore, because a node of HSM represents a spherical region, intersection between, two nodes can be easily found just by calculating the distance between two spheres corresponding to them no matter how the objects move. Finally, the efficiency of the algorithm is demonstrated by several experiments.

Collision–Free Trajectory Planning for Two Robot Arms

SUMMARYAn approach for collision–free trajectory planning along designated paths of two robots in a common workspace is presented. Specifically, in order to describe potential collision between the links of two robots along the designated paths, explicit forms of virtual obstacle are adopted, according to which links of one robot are made to grow while the other robot is forced to shrink as a point on the path. Then, a notion of virtual coordination space is introduced to visualize all the collision–free coordinations of two trajectories. Assuming that a collision–free coordination curve between the two robots is given via a virtual coordination space, the minimum time collision–free trajectory pair for the two robots is sought considering dynamic constraints of torque and velocity bounds of actuators of the two robots.