Avoidance Control Law Research Articles

Guaranteed real-time cooperative collision avoidance for n-DOF manipulators

Abstract This paper presents a decentralized, cooperative, real-time avoidance control strategy for robotic manipulators. The proposed avoidance control law builds on the concepts of artificial potential field functions and provides tighter bounds on the minimum safe distance when compared to traditional potential-based controllers. Moreover, the proposed avoidance control law is given in analytical, continuous closed form, avoiding the use of optimization techniques and discrete algorithms, and is rigorously proven to guarantee collision avoidance at all times. Examples of planar and 3D manipulators with cylindrical links under the proposed avoidance control are given and compared with the traditional approach of modeling links and obstacles with multiple spheres. The results show that the proposed avoidance control law can achieve, in general, faster convergence, smaller tracking errors, and lower control torques than the traditional approach. Furthermore, we provide extensions of the avoidance control to robotic manipulators with bounded control torques.

Formation Control of Mobile Robots Based on Pin Control of Complex Networks

Robot formation control has several advantages that make it interesting for research. Multiple works have been published in the literature using different control approaches. This work presents the control of different groups of robots to achieve a desired formation based on pinning control of complex networks and coordinate translation. The implemented control law comprises complex network bounding, proportional, and collision avoidance terms. The tests for this proposal were performed via simulation and experimental tests, considering different networks of differential robots. The selected robots are Turtlebot3® Waffle Pi robots. The Turtlebot3® Waffle Pi is a differential mobile robot with the Robot Operating System (ROS). It has a light detection and ranging (LiDAR) sensor used to compute the collision avoidance control law term. Tests show favorable results on different formations testing on various groups of robots, each composed of a different number of robots. From this work, implementation on other devices can be derived, as well as trajectory tracking once in formation, among other applications.

Cooperative Target Enclosing and Tracking Control with Obstacles Avoidance for Multiple Nonholonomic Mobile Robots

This paper investigates the cooperative control problem for a group of autonomous nonholonomic mobile robots, in which the robots are required to collaboratively enclose and track a stationary or moving target in a circular formation. In order to solve the challenging problem that the robots with speed constraints move uniformly to the exact position on the circles centered on the target while avoiding obstacles encountered, a distributed coupling controller scheme consisting of target encircling, phase positioning and spacing assignment, and the avoidance of obstacles is proposed. First, a novel circular motion control law based on the feedback control idea of trajectory tracking is proposed, which guides all robots move to the target-centered circles and maintains the expected distances between the robots and the target. Second, a phase positioning and spacing assignment control law by introducing a nonlinear function is proposed, which can be coupled into the circular motion controller to implement the robots converge to the specified position on the circles. Finally, the obstacles avoidance control law based on artificial potential field only with repulsive force is adopted to ensure each robot effectively avoids obstacles. The rigorous theoretical analysis of the convergence of the proposed controller is given, and then the simulations and experiments are provided to validate the effectiveness and applicability of the proposed control scheme.

Intelligent controller for nonholonomic wheeled mobile robot: A fuzzy path following combination

This research article presents a novel solution of controller design for the autonomous path-following maneuver of a nonholonomic wheeled mobile robotic (WMR) system subjected to static and dynamic obstacles. Currently, autonomously operated nonholonomic vehicles, capable of completing tasks avoiding collisions, are deployed for low-profile household applications to sophisticated space missions. The geometrically constrained path-following controller with embedded intelligence for collision avoidance is designed based on a twofold hybrid control law. The hybrid control law combines the feedback linearization controller (FBC) with the fuzzy logic controller (FLC). The feedback linearization controller helps the mobile robot to remain on its desired path, while the fuzzy logic controller helps the mobile robot to avoid critical obstacles around the reference path. It is analytically proven that the proposed hybrid control law converges the robot asymptotically to the desired path when it is safely away from obstacles. Further, when the robot detects an obstacle in its sensing range, obstacle avoidance control law acts locally and it deviates itself from the desired path to avoid collision assuring stability through a bounded tracking control law. Considering bounded sensor measurement uncertainties during obstacle detection, it is observed that the fuzzy logic-based collision-avoidance algorithm behaves in a robust manner. The hybrid controller is designed and tested in a simulated environment with the real-life parameters of a nonholonomic wheeled mobile robot. The robot is capable of traversing through the geometrically constrained desired paths avoiding obstacles in an improved manner compared to the existing method. Moreover, the robot is also capable of returning back to its original path when obstacles are safely away. The performance of the novel hybrid control strategy is illustrated for several geometrically constrained paths via simulation to show its effectiveness in terms of fulfilling dual objectives of path following and simultaneous collision avoidance in an improved manner.

Anti-collision zone division based hazard avoidance guidance for asteroid landing with constant thrust

Future asteroid landing and sample return missions will seek for landing sites with high scientific value, such as hazardous terrains, which means that the spacecraft needs the ability of autonomous hazard avoidance. Nowadays, the guidance algorithm based on artificial potential function plays an increasingly important role in hazard avoidance, but the local minimum problem makes that the spacecraft cannot reach the desired target landing point in some complex terrains. In this paper, a novel hazard avoidance guidance method which improves the traditional artificial potential function is developed. This method focuses on the impact zone analysis of hazards and defines anti-collision zone. In addition, a new repulsive potential function in logarithmic form is designed with continuity and fast numerical change rate in the anti-collision zone on this basis, and the problem of spacecraft falling into local minimum zone in complex terrains can be effectively avoided. Considering the practical application of constant thrust engine, the hazard avoidance control law with constant thrust sliding mode is designed to reduce switching frequency and fuel consumption. The performance of the proposed guidance law is verified through a set of simulations, as well as the global stability of the control system under uncertainty and perturbation conditions.

Adaptive Obstacle Avoidance for a Class of Collaborative Robots

In a human–robot collaboration scenario, operator safety is the main problem and must be guaranteed under all conditions. Collision avoidance control techniques are essential to improve operator safety and robot flexibility by preventing impacts that can occur between the robot and humans or with objects inadvertently left within the operational workspace. On this basis, collision avoidance algorithms for moving obstacles are presented in this paper: inspired by algorithms already developed by the authors for planar manipulators, algorithms are adapted for the 6-DOF collaborative manipulators by Universal Robots, and some new contributions are introduced. First, in this work, the safety region wrapping each link of the manipulator assumes a cylindrical shape whose radius varies according to the speed of the colliding obstacle, so that dynamical obstacles are avoided with increased safety regions in order to reduce the risk, whereas fixed obstacles allow us to use smaller safety regions, facilitating the motion of the robot. In addition, three different modalities for the collision avoidance control law are proposed, which differ in the type of motion admitted for the perturbation of the end-effector: the general mode allows for a 6-DOF perturbation, but restrictions can be imposed on the orientation part of the avoidance motion using 4-DOF or 3-DOF modes. In order to demonstrate the effectiveness of the control strategy, simulations with dynamic and fixed obstacles are presented and discussed. Simulations are also used to estimate the required computational effort in order to verify the transferability to a real system.

Cooperative Collision Avoidance Control of Servo/IPMC Driven Robotic Fish With Back-Relaxation Effect

In this letter, a collision avoidance control strategy is developed for a robotic fish that is propelled by a two-joint fishtail, comprising a servo motor and an ionic polymer-metal composite (IPMC), which are used as solid and soft actuators, respectively. In this dual-actuator system, the forward motion of the fish is controlled by the servo motor, which generates a flapping motion at its first joint, and the turning motion of the fish is controlled by bending the IPMC at its second joint. When a constant voltage is applied to the IPMC, the robotic fish is observed to demonstrate a short-term turning characteristic, and this is attributed to the back-relaxation phenomenon inherent in the IPMC. In order to capture this unique characteristic, a data-driven approach is adopted to model the fish's lateral acceleration response when subjected to an IPMC voltage input. Experimental tests, including bending tests on an individual IPMC slice and turning tests on the robotic fish (with the servo/IPMC tail), are conducted to collect sufficient data to identify a transfer function that relates the voltage applied to the IPMC with the lateral acceleration response of the fish. This transfer function is then integrated with a collision avoidance control law (based on the collision cone concept) to determine the IPMC voltages for a pair of robotic fish to avoid collisions. Experiments are performed to validate the collision avoidance control law.

Hybrid Attitude Control for Nano-Spacecraft: Reaction Wheel Failure and Singularity Handling

This paper addresses the attitude control of nano-spacecraft with three reaction wheels and three magnetorquers in low Earth orbits, and develops algorithms to maintain control when any one of the reaction wheels completely fails. In the event of a reaction wheel failure, it is shown that the key challenge of maintaining accurate autonomous three-axis tracking is a problem of singularity avoidance in control allocation. In particular, control law singularities occur depending on the type of orbit, the environment, and the attitude, where the system is no longer controllable. Two algorithmic singularity avoidance techniques based on singularity prediction and artifici‘al potential functions are proposed. In addition, an optimized reaction wheel configuration is proposed to enhance singularity avoidance capability. To illustrate the effectiveness of the singularity avoidance control laws, they are tested in simulations that include the effects of perturbing environmental torques, reaction wheel jitter, and actuator misalignment.

Filtered adaptive constrained sampled‐data control for uncertain multivariable nonlinear systems

AbstractA filtered adaptive constrained sampled‐data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low‐pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed‐loop system with the sampled‐data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled‐data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out.

Consensus Formation Control and Obstacle Avoidance of Multiagent Systems with Directed Topology

This study addresses the problems of formation control and obstacle avoidance for a class of second-order multiagent systems with directed topology. Formation and velocity control laws are designed to solve the formation tracking problem. A new obstacle avoidance control law is also proposed to avoid obstacles. Then, the consensus control protocol consists of the formation, velocity, and obstacle avoidance control laws. The convergence of the proposed control protocol is analyzed by a redesigned Lyapunov function. Finally, the effectiveness of theoretical results is illustrated by simulation examples. The simulation results show that the formation tracking problem of the given multiagent systems can be realized and obstacles can be avoided under the proposed control protocol.

Cooperative Avoidance Control With Velocity-Based Detection Regions

Guaranteed collision avoidance control laws for multi-agent systems typically rely on constant detection regions. This constraint tends to generate conservative and slower agents’ trajectories. To reduce the conservatism of avoidance control laws, this letter presents two decentralized, cooperative strategies for arbitrarily large groups of agents that decrease the vehicles’ effective detection regions by using velocity information. The vehicles are modeled as a class of nonlinear Lagrangian systems which full state vector represents absolute position. The control laws are proven to guarantee collision avoidance at all times and are shown to be more energy-efficient and to generate faster and smoother trajectories than traditional methods. Moreover, by decreasing the detection regions, the agents are able to converge to destinations closer to each other’s avoidance regions, a feature not possible with traditional avoidance control.

Discrete-time predictive trajectory tracking control for nonholonomic mobile robots with obstacle avoidance

This article presents a tracking control approach with obstacle avoidance for a mobile robot. The control law is composed of two parts. The first is a discrete-time model predictive method-based trajectory tracking control law that is derived using an optimal quadratic algorithm. The second part is the obstacle avoidance strategies that switch according to two different designed obstacle avoidance regions. The controllability of the avoidance control law is analyzed. The simulation results validate the effectiveness of the proposed control law considering both trajectory tracking and obstacle avoidance.

Cooperative Exploration and Networking While Preserving Collision Avoidance.

Monitoring of large complex environments, such as underwater environments, is an important task in surveillance. An information (sensor) network can be built to achieve the task. To build an information network in an unknown workspace, we use multiple robots deploying information nodes. While robots build the network, they localize themselves as well as deployed nodes in the global coordinate system. Our multirobot networking strategy is as follows: each robot iteratively visits a frontier, which borders an unsensed area, until all areas are explored. As multiple robots explore the workspace, a robot must avoid colliding with another robot as well as with an obstacle. Hence, we introduce collision avoidance control laws and integrate the control laws with our cooperative networking strategy. Using MATLAB simulations, we verify the scalability and effectiveness of both our networking strategy and the collision avoidance control laws.

Computationaly Simple Obstacle Avoidance Control Law for Small Unmanned Aerial Vehicles

Abstract The investigations of the system which allow to avoid obstacles by the unmanned aerial vehicles (UAV) are presented in the paper. The system is designed to enable the full autonomous UAV flight in an unknown environment. As an information source about obstacles digital camera was used. Developed algorithm uses the existing relations between the imaging system and the parameters read from the UAV autopilot. Synthesis of the proposed obstacle avoidance control law was oriented for computational simplicity. Presented algorithm was checked during simulation studies and in-flight tests.

Motion Coordination of AGV's in FMS using Petri Nets

This paper proposes a modeling strategy for automated Flexible Manufacturing Systems (FMS) that incorporates automated guided vehicles (AGV's) as material handling systems. Using the industrial standard ISA-95, the task-based coordination of equipment and storages is constructed considering process restrictions, logical precedence conditions, shared resources and the assignment of the robots to move work pieces individually or in subgroups. The Petri Net model calls in the low level to formation, marching and collision avoidance control laws, for omnidirectional robots. The hybrid architecture is implemented and validated for the case of a FMS and four mobile robots.

Trajectory tracking with collision avoidance for nonholonomic vehicles with acceleration constraints and limited sensing

Nowadays, autonomously operated nonholonomic vehicles are employed in a wide range of applications, ranging from relatively simple household chores (e.g. carpet vacuuming and lawn mowing) to highly sophisticated assignments (e.g. outer space exploration and combat missions). Each application may require different levels of accuracy and capabilities from the vehicles, yet, all expect the same critical outcome: to safely complete the task while avoiding collisions with obstacles and the environment. Herein, we report on a bounded control law for nonholonomic systems of unicycle-type that satisfactorily drive a vehicle along a desired trajectory while guaranteeing a minimum safe distance from another vehicle or obstacle at all times. The control law is comprised of two parts. The first is a trajectory tracking and set-point stabilization control law that accounts for the vehicle’s kinematic and dynamic constraints (i.e. restrictions on velocity and acceleration). We show that the bounded tracking control law enforces global asymptotic convergence to the desired trajectory and local exponential stability of the full state vector in the case of set-point stabilization. The second part is a real-time avoidance control law that guarantees collision-free transit for the vehicle in noncooperative and cooperative scenarios independently of bounded uncertainties and errors in the obstacles’ detection process. The avoidance control acts locally, meaning that it is only active when an obstacle is close and null when the obstacle is safely away. Moreover, the avoidance control is designed according to the vehicle’s acceleration limits to compensate for lags in the vehicle’s reaction time. The performance of the synthesized control law is then evaluated and validated via simulation and experimental tests.

Obstacle and Collision Avoidance Control Laws of a Swarm of Boids

This paper proposes a new obstacle and collision avoidance control laws for a three-dimensional swarm of boids. The swarm exhibit collective emergent behaviors whilst avoiding the obstacles in the workspace. While flocking, animals group up in order to do various tasks and even a greater chance of evading predators. A generalized algorithms for attraction to the centroid, inter-individual swarm avoidance and obstacle avoidance is designed in this paper. We present a set of new continuous time-invariant velocity control laws is presented which is formulated via the Lyapunov-based control scheme. The control laws proposed in this paper also ensures practical stability of the system. The effectiveness of the proposed control laws is demonstrated via computer simulations.

Obstacle and Collision Avoidance Control Laws of a Swarm of Boids

Obstacle and Collision Avoidance Control Laws of a Swarm of Boids

Experiment of Collision Avoidance Control Law with Information Amount Feedback Using Vehicle Model

This paper is on the experiment of collision avoidance control law with information amount feedback using vehicle model. The collision avoidance is key technology for future mass transportation systems. The amount of information obtained by the evader as a physical value for the collision avoidance feedback is used in this study. This will lower the risk when the intruder is coming in from out-of-sight. This paper will demonstrate the effect of collision avoidance control with information amount feedback using vehicle model. The results show that the control law works in the actual environment for collision avoidance with similar motion with that of humans.

Active Collision Avoidance Control for Fractionated Satellite Clusters in Ellipse Orbit

The active collision avoidance maneuver of fractionated satellite cluster is studied. Especially, two clusters with different structure configuration in ellipse orbit and the collision description method between them are discussed. Due to the limitation of the collision probability based on the minimum distance, a new method is developed which including the effect of relative velocity on collision. Only J2 perturbation is considered in the relative dynamics and a PD controller based on BP neural network using automatic differentiation method is adopted when a collision is imminent. The simulation results validate that the presented active collision avoidance control law is effective.