Highly smooth and parameter independent obstacle avoidance method for autonomous vehicle with velocity-varying obstacle

One of the primary challenges for autonomous vehicle (AV) is planning a collision-free path in dynamic environment. It is a tricky task for achieving high-performance obstacle avoidance with velocity-varying obstacle. To solve this problem, a highly smooth and parameter independent obstacle avoidance method for autonomous vehicle with velocity-varying obstacle (HSPI-OAM) is presented in this work. The proposed method uses the virtual collision point model to accurately design the desired acceleration, which makes the obtained path highly smooth. At the same time, the method gets rid of the dependence on parameter adjustment and has strong adaptability to different environments. The simulation is implemented on the Matlab-Carsim co-simulation platform, and the simulation results show that the path planned by HSPI-OAM has good performance for obstacle with acceleration.

Fixed-time consensus of nonlinear multi-agent system with uncertain disturbances based on event-triggered strategy

This paper presents a fixed-time consensus problem for multi-agent systems (MASs) with nonlinear dynamics and uncertain disturbances, the event-triggered strategy is proposed to address this issue. Firstly, based on event-triggered control theory, a fixed-time consensus protocol is proposed, which can avoid continuous communication and greatly reduces the power consumption of proposed protocols. Secondly, based on graph topology, fixed-time control method and Lyapunov theory, the novel fixed-time consensus criteria of MASs with nonlinearity under Lipschitz condition and uncertain disturbances bounds is derived via the designed protocols. Furthermore, the consensus can be guaranteed by setting the proper parameters, it should be pointed out that for any given initial state, the MASs can reach consensus within the setting time. Thirdly, by utilizing the above control strategy, the MASs have no Zeno behavior. Finally, two simulation examples and the practical application of unmanned air vehicles (UAVs) verify the reliability of proposed control scheme.

Dead-Zone ESO Based Sensorless Force/Position Control for Dynamic Contact Systems

In this paper, the sensorless force/position control problem is investigated for a general class of dynamic contact systems with both motion sensor noise and unknown kinetic friction by designing a force observer-based controller. Firstly, in order to suppress the effect of motion sensor noise, a dead-zone extended state observer (ESO) is introduced, and the contact force is estimated. Then, based on the force estimate, a controller is designed to realize force/position tracking control, where the parameters of the observer and controller are obtained by a linear matrix inequality (LMI) method. The sufficient conditions are provided to ensure the stability of the closed-loop system in terms of LMIs. Finally, a numerical simulation is carried out to illustrate the applicability and effectiveness of the proposed method.

Review of wheeled mobile robot collision avoidance under unknown environment

Recently, the working scenes of the robot have been emerging as diversity and complexity with gradually mature of robotic control technology. The challenge of robot adaptability emerges, especially in complicated and unknown environments. Among the numerous researches on improving the adaptability of robots, aiming at avoiding collision between robot and external environment, obstacle avoidance has drawn much attention. Compared to the global circumvention requiring the environmental information that is known, the local obstacle avoidance is a promising method due to the environment is possibly dynamic and unknown. This study is aimed at making a review of research progress about local obstacle avoidance methods for wheeled mobile robots (WMRs) under complex unknown environment in the last 20 years. Sensor-based obstacle perception and identification is first introduced. Then, obstacle avoidance methods related to WMRs' motion control are reviewed, mainly including artificial potential field (APF)-based, population-involved meta heuristic-based, artificial neural network (ANN)-based, fuzzy logic (FL)-based and quadratic optimization-based, etc. Next, the relevant research on Unmanned Ground Vehicles (UGVs) is surveyed. Finally, conclusion and prospection are given. Appropriate obstacle avoidance methods should be chosen based on the specific requirements or criterion. For the moment, effective fusion of multiple obstacle avoidance methods is becoming a promising method.

Coupled fractional-order sliding mode control and obstacle avoidance of a four-wheeled steerable mobile robot

Recently, four-wheeled steerable mobile robots (FSMR) have attracted increasing attention in industrial fields, however the collision-free trajectory tracking control is still challenging in dynamic environments. This paper studies a new coupled fractional-order sliding mode control (CFSMC) and obstacle avoidance scheme, which has superior capacities of providing more control flexibilities and achieving high-accuracy. Instead of exploring traditional integer-order solutions, novel fractional-order sliding surfaces are proposed to handle the nonlinear interconnected states in a coupled structure. To accomplish non-oscillating avoidance of both stationary and moving entities within an uncertain workspace, a modified near-time-optimal potential function is subsequently presented with improved efficiency and reduced collision-resolving distances. By utilizing fuzzy rules, proper adaption gains of the reaching laws are designed to degenerate the effect of undesired chattering. The asymptotic stability and convergence can be guaranteed for the resultant closed-loop system. Three experiments are implemented on a real-time FSMR system. The results validate the reliability of the presented CFSMC scheme in terms of significantly mitigated following errors, faster disturbance rejection and smooth transition as compared to conventional methods.

A review of algorithms and techniques for image-based recognition and inference in mobile robotic systems

Autonomous vehicles include driverless, self-driving and robotic cars, and other platforms capable of sensing and interacting with its environment and navigating without human help. On the other hand, semiautonomous vehicles achieve partial realization of autonomy with human intervention, for example, in driver-assisted vehicles. Autonomous vehicles first interact with their surrounding using mounted sensors. Typically, visual sensors are used to acquire images, and computer vision techniques, signal processing, machine learning, and other techniques are applied to acquire, process, and extract information. The control subsystem interprets sensory information to identify appropriate navigation path to its destination and action plan to carry out tasks. Feedbacks are also elicited from the environment to improve upon its behavior. To increase sensing accuracy, autonomous vehicles are equipped with many sensors [light detection and ranging (LiDARs), infrared, sonar, inertial measurement units, etc.], as well as communication subsystem. Autonomous vehicles face several challenges such as unknown environments, blind spots (unseen views), non-line-of-sight scenarios, poor performance of sensors due to weather conditions, sensor errors, false alarms, limited energy, limited computational resources, algorithmic complexity, human–machine communications, size, and weight constraints. To tackle these problems, several algorithmic approaches have been implemented covering design of sensors, processing, control, and navigation. The review seeks to provide up-to-date information on the requirements, algorithms, and main challenges in the use of machine vision–based techniques for navigation and control in autonomous vehicles. An application using land-based vehicle as an Internet of Thing-enabled platform for pedestrian detection and tracking is also presented.

Fractional-order internal model control algorithm based on the force/position control structure of redundant actuation parallel robot

This article proposes a new control structure for the complex redundant actuation parallel robot based on force/position hybrid control structure. The traditional proportional–integral–derivative control method, integer-order internal model control method and fractional-filter internal model control–proportional–derivative control method are used in the position structure of force/position hybrid control. The fractional-filter internal model control–proportional–derivative control method is used in the position loop of the permanent magnet synchronous motor to reduce the position error. A fractional-order theory with the internal model control method is used in redundant actuation force control structure, which can improve the control precision of the driving force of the parallel robot. The Admas/Matlab simulation results show that the proposed method outperforms other methods and can obtain good robustness and tracking performance.

A New Conflict Resolution Method for Multiple Mobile Robots in Cluttered Environments With Motion-Liveness

This paper presents a new conflict resolution methodology for multiple mobile robots while ensuring their motion-liveness, especially for cluttered and dynamic environments. Our method constructs a mathematical formulation in a form of an optimization problem by minimizing the overall travel times of the robots subject to resolving all the conflicts in their motion. This optimization problem can be easily solved through coordinating only the robots' speeds. To overcome the computational cost in executing the algorithm for very cluttered environments, we develop an innovative method through clustering the environment into independent subproblems that can be solved using parallel programming techniques. We demonstrate the scalability of our approach through performing extensive simulations. Simulation results showed that our proposed method is capable of resolving the conflicts of 100 robots in less than 1.23 s in a cluttered environment that has 4357 intersections in the paths of the robots. We also developed an experimental testbed and demonstrated that our approach can be implemented in real time. We finally compared our approach with other existing methods in the literature both quantitatively and qualitatively. This comparison shows while our approach is mathematically sound, it is more computationally efficient, scalable for very large number of robots, and guarantees the live and smooth motion of robots.

An approach for real-time motion planning of an inchworm robot in complex steel bridge environments

Path planning can be difficult and time consuming for inchworm robots especially when operating in complex 3D environments such as steel bridges. Confined areas may prevent a robot from extensively searching the environment by limiting its mobility. An approach for real-time path planning is presented. This approach first uses the concept of line-of-sight (LoS) to find waypoints from the start pose to the end node. It then plans smooth, collision-free motion for a robot to move between waypoints using a 3D-F2algorithm. Extensive simulations and experiments are conducted in 2D and 3D scenarios to verify the approach.

A Cross-Domain Survey of Metrics for Modelling and Evaluating Collisions

This paper provides a brief survey of the metrics for measuring probability, degree, and severity of collisions as applied to autonomous and intelligent systems. Though not exhaustive, this survey evaluates the state-of-the-art of collision metrics, and assesses which are likely to aid in the establishment and support of autonomous system collision modelling. The survey includes metrics for 1) robot arms; 2) mobile robot platforms; 3) nonholonomic physical systems such as ground vehicles, aircraft, and naval vessels, and; 4) virtual and mathematical models.

Vision Servoing Based on the Density Analysis of Texture Elements

We present a novel vision servoing method, which is fit for climbing robots and those in unstructured environments, based on texture analysis. A large textured area is the target for observation. After the definition of texture element distribution density, the relationship between the change of the density at some selected points and the camera pose is deduced. The vision servoing control law, which meets the requirement of Lyapunov stability is designed in this paper. Experiments show the effectiveness of this method.

Force Sensor of a Climbing Robot Derived from Its Own Flexible Structure

One of the most important design constraints of a climbing robot is its own weight. When links or legs are used as a locomotion system they tend to be composed of special lightweight materials, or four-bars-linkage mechanisms are designed to reduce the weight with small rigidity looses. In these cases, flexibility appears and undesirable effects, such as dynamics vibrations, must be avoided at least when the robot moves at low speeds. The knowledge of the real tip position requires the computation of its compliance or stiffness matrix and the external forces applied to the structure. Gravitational forces can be estimated, but external tip forces need to be measured. This paper proposes a strain gauge system which achieves the following tasks: (i) measurement of the external tip forces, and (ii) estimation of the real tip position (including flexibility effects). The main advantages of the proposed system are: (a) the use of external force sensors is avoided, and (b) a substantial reduction of the robot weight is achieved in comparison with other external force measurement systems. The proposed method is applied to a real symmetric climbing robot and experimental results are presented.

Flexible Structural Design for Side-Sliding Force Reduction for a Caterpillar Climbing Robot

Due to sliding force arising from the closed chain mechanism among the adhering points of a climbing caterpillar robot (CCR), a sliding phenomenon will happen at the adhering points, e.g., the vacuum pads or claws holding the surface. This sliding force makes the attachment of the climbing robot unsteady and reducesthe motion efficiency. According to the new bionic research on the soft-body structure of caterpillars, some flexible structures made of natural rubber bars are applied in CCRs correspondingly as an improvement to the old rigid mechanical design of the robotic structure. This paper firstly establishes the static model of the sliding forces, the distortion of flexible bars and the driving torques of joints. Then, a method to reduce the sliding force by exerting a compensating angle to an active joint of the CCR is presented. The analyses and experimental results indicate that the flexible structure and the compensating angle method can reduce the sliding forces remarkably.