Virtual Potential Field Research Articles

Tripping Avoidance Lower Extremity Exoskeleton Based on Virtual Potential Field for Elderly People.

Tripping is a common problem that everyone faces when walking. This paper mainly focuses on a lower limb exoskeleton that can help those weak in joints to avoid tripping when negotiating stairs or stepping over obstacles. This method does not need a camera or map reconstruction to recognize the obstacles and plan paths. The exoskeleton applies an impedance controller to follow and control the pilot’s movements. A virtual potential field is proposed to help the robot regulate the pilot’s motion and avoid kicking the obstacles appearing in front of the pilot’s foot during walking. Simulation and experiments show that this method works effectively and could help the elderly and those affected by joint weakness avoid tripping when walking.

A Semi-Autonomous Stereotactic Brain Biopsy Robot With Enhanced Safety

In stereotactic brain biopsy, operating the needle accurately and taking the biopsy specimen safely are two major challenges for ensuring the success of the surgical procedure. Considering this fact, surgical robots offering high accuracy and precision have been developed for neurosurgery including brain biopsy. Typical brain biopsy robots are only commanded to adjust the needle's pose before inserting the needle manually by a neurosurgeon. In the literature, there exists no robotic system that is competent to complete the needle insertion task autonomously. To move a step forward, a novel biopsy module for brain biopsy is first designed and fabricated in this paper. The biopsy module can be automated to complete a series of tasks such as inserting the needle, generating and controlling the aspiration pressure for specimen acquisition, and rotating the cannula for side-cutting. The biopsy module is further integrated with a cost-effective and lightweight UR5 robot and an optical tracking system to improve the autonomy, leading to a stereotactic neuronavigation system. Kinematic relationships of the involved elements are established via a calibration process. A quadratic programming based approach equipped with a virtual potential field method is implemented to safely control the robot with joint-limit avoidance and obstacle avoidance capabilities. The experimentation of the brain biopsy robot is performed, demonstrating that the developed robotic system has potential applicability in the brain biopsy surgery.

Intrusion Detection Based on <inline-formula> <tex-math notation="LaTeX">$k$</tex-math> </inline-formula>-Coverage in Mobile Sensor Networks With Empowered Intruders

Intrusion detection is one of the important applications of wireless sensor networks (WSNs). Prior research indicated that the barrier coverage method combined with mobile sensor networks (MSNs) can enhance the effectiveness of intrusion detection by mitigating coverage holes commonly appearing in stationary WSNs. However, the trajectories of moving sensors and moving intruders have not been investigated thoroughly, whereas the impact between two adjacent moving sensors and between a moving sensor and a moving intruder are still under-determined. In order to address these open problems, in this paper, we firstly discuss the virtual potential field between sensors as well as between sensors and intruders. We then propose to formulate the mobility pattern of sensor node using elastic collision model and that of intruder using point charge model. The point charge model describes an hitherto unexplored mobility pattern of empowered intruders, which are capable of acting upon the virtual repulsive forces from sensors in order to hide them away from being detected. With the aid of the two models developed, analytical expressions and simulation results demonstrate that our proposed design achieves a higher $k$ -barrier coverage probability in intrusion detection compared to that of the conventional designs. It is also worth mentioning that these improvements are achieved with shorter average displacement distance and under much more challenging MSNs settings.

Routing algorithm for supporting data-differentiated service in hybrid wireless mesh networks in underground mines

Hybrid wireless mesh networks are more suitable to tunnels in underground mines because mesh clients can perform the routing functionality and provide end-user applications. Types of data transmitted among hybrid wireless mesh networks in underground mines are diverse and power supply of clients is limited. Using virtual potential field, a routing algorithm is proposed to support data-differentiated service in hybrid wireless mesh networks. Based on network parameters, the hybrid wireless mesh networks are abstracted as potential fields. The hop count is used to build the depth potential field. The residual energy of nodes is converted into penalty factor to symbolize the used buffer spaces of nodes, which is used to construct resource potential field to support different types of data. According to the different demands of data transmission, the proportion of these two potential fields is adjusted by a regulatory factor to form a hybrid potential field. The data packets are driven to move toward the gateway in the hybrid potential field at the same time to achieve high quality of service. Simulation results demonstrate that the proposed routing algorithm has shown better performance on end-to-end delay, delivery ratio, and network lifetime, compared with similar algorithms.

Traffic aware field-based routing for wireless sensor networks

Route estimation process often involves significant message exchanges among wireless sensor nodes while selecting the least cost path. Nodes along this path handle more traffic that leads to death of battery powered nodes and shortening network life. Thus, routing mechanisms for wireless sensor network (WSN) must be traffic aware and at the same time, the alternate route(s) incur less delay overhead. This paper considers a query-driven application scenario in WSN where the sink diffuses query over the network to fetch information. A novel field-based routing (FBR) mechanism is proposed that inherits the physical properties of Coulomb’s law for point charges in free space. It defines a distance field parameter corresponding to each sensor node with respect to the sink. The sink being the negatively charged particle the packets from sensor nodes (positively charged particle) flow towards the field generating sink. The algorithm considers energy depletion rate for estimating the virtual potential field at nodes so as to avoid the nodes having less remaining energy. Further, the gradient updation is based on the local information which results in less message complexity (O(n)) and low computation overhead, which is comparable to the best available approaches. NS-2 based simulation demonstrates a significant enhancement in network lifetime, increased packet reception ratio and reduction in energy dissipation rate making the FBR mechanism suitable for WSN.

Comprehensive predictive control method for automated vehicles in dynamic traffic circumstances

Motion control problems remain to be fully solved for automated vehicles in dynamic traffic circumstances. Existing approaches usually first make a driving behaviour decision, then design a reference trajectory that may not match the vehicle dynamic constraints explicitly and finally adopt a local feedback control method to track the reference. Important commands may be lost or not well translated in the process of information exchange and transmission. Moreover, multiple methods specifically designed for different tasks may not cooperate well in one system. In this study, the authors propose a comprehensive predictive control method which can directly generate the control commands from the traffic circumstance and the vehicle dynamics, without involving any driving decision-making modules and any predefined reference trajectories. Virtual potential fields are introduced to model the traffic circumstance including the road boundaries, lane markings and moving obstacle vehicles. A model predictive control problem is formulated with the overall potential function and constraints including the vehicle dynamics and the safety distances between the ego vehicle and other vehicles. Lane keeping, lane changing, car following and overtaking driving behaviours are simulated in different scenarios. Results show that this method is capable of controlling the automated vehicle in different traffic circumstances.

Cooperative multi‐agent sweep coverage control for unknown areas of irregular shape

The study solves multi-agent cooperative control problems of covering irregularly-shaped unknown areas. A sweep coverage motion scheme is proposed: the agents are arranged in a row across the area and sweep through. The formation is flexible thus the agents can be scattered across the widest part and can queue up to pass through the narrowest portion. This allows the agents to cover the region by collectively passing through it only once, which may help to improve the survivability of reconnaissance vehicles. A distributed second-order control law is designed by modelling the agents as point masses in planar space. The approach is inspired by the motion of a string of balls connected by springs, thus virtual elastic force and potential field are applied to the agents, which introduces non-linearity to the system. Complete coverage as well as collision avoidance among agents and borders are guaranteed by parameter constraints that provided and validated via theoretical deduction and numerical simulations. Compared with the existing unknown-area coverage methods by randomly exploring the area, the proposed one yields more regular motion paths. Limitations of the work and future research directions are finally concluded.

Motion Planning with Energy Reduction for a Floating Robotic Platform Under Disturbances and Measurement Noise Using Reinforcement Learning

This paper investigates the use of reinforcement learning for the navigation of an over-actuated, i.e. more control inputs than degrees of freedom, marine platform in unknown environment. The proposed approach uses an online least-squared policy iteration scheme for value function approximation in order to estimate optimal policy, in conjunction with a low-level control system that controls the magnitude of the linear velocity, and the orientation of the platform. Primary goal of the proposed scheme is the reduction of the consumed energy. To that end, we propose a variable reward function that depends on the energy consumption of the platform. We evaluate our approach in a complex and realistic simulation environment and report results concerning its performance on estimating optimal navigation policies under different environmental disturbances, and position GPS measurement noise. The proposed framework is compared, in terms of energy consumption, to a baseline approach based on virtual potential fields. The results show that the marine platform successfully discovers the target point following a sub-optimal path, maintaining reduced energy consumption.

Lateral acceleration potential field function control for rollover safety of multi-wheel military vehicle with in-wheel-motors

This article proposes an automatic longitudinal deceleration based method for multi-wheel vehicle rollover safety in autonomous mode. The information of lateral acceleration and vehicle roll angle is used to generate the longitudinal acceleration at which the vehicle will remain stable to rollover. The lateral and roll dynamics are coupled with longitudinal dynamics using a potential field function for lateral acceleration. This virtual potential field is developed on g-g diagram which represents vehicle portrait of lateral and longitudinal acceleration on abscissa and ordinate respectively. The motion of vehicle is represented by a point moving on this phase portrait of g-g diagram. TruckSim model of multi-wheel military vehicle with in-wheel motors is used with this algorithm which shows that the vehicle is less susceptible to rollover. The safe longitudinal acceleration is achieved by torque control of in-wheel motors fitted in each wheel. Using this method, the vehicle followed the desired trajectory as higher speeds which are safe. This is particularly useful for vehicle autonomous driving with rollover stability.

Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints

A path planning and tracking framework is presented to maintain a collision-free path for autonomous vehicles. For path-planning approaches, a 3-D virtual dangerous potential field is constructed as a superposition of trigonometric functions of the road and the exponential function of obstacles, which can generate a desired trajectory for collision avoidance when a vehicle collision with obstacles is likely to happen. Next, to track the planned trajectory for collision avoidance maneuvers, the path-tracking controller formulated the tracking task as a multiconstrained model predictive control (MMPC) problem and calculated the front steering angle to prevent the vehicle from colliding with a moving obstacle vehicle. Simulink and CarSim simulations are conducted in the case where moving obstacles exist. The simulation results show that the proposed path-planning approach is effective for many driving scenarios, and the MMPC-based path-tracking controller provides dynamic tracking performance and maintains good maneuverability.

Nonlinear MPC Controller Design for AIR Supply of PEM Fuel Cell Based Power Systems

AbstractThe air supply system, which provides the oxygen for the fuel cell stack, is one of the most important subsystems of the proton exchange membrane fuel cell (PEMFC). In order to improve the performance of the air supply, a small rechargeable lithium‐ion battery is utilized to start up the PEMFC system and provide buffer power supply for the load demand. With energy consumption of the compressor considered, a power coordinating algorithm utilizing a virtual potential field approach is presented to manage the power demand for the PEMFC and the battery while maintaining the battery's state of charge. A nonlinear observer is designed to estimate the unmeasurable states of the air supply system and its convergence is proven. A nonlinear MPC method is proposed to control the air flow and ensure the adequate oxygen supply. Simulation results are provided to validate the performance of the power management algorithm and the air supply control method. Compared with the results of the MPC algorithm and the nonlinear MPC method for the PEMFC system without an auxiliary battery, the method designed here has better performance.

Self-organizing control strategy for asteroid intelligent detection swarm based on attraction and repulsion

The self-organizing control strategy for asteroid intelligent detection swarm, which is considered as a space application instance of intelligent swarm, is developed. The leader-follower model for the asteroid intelligent detection swarm is established, and the further analysis is conducted for massive asteroid and small asteroid. For a massive asteroid, the leader spacecraft flies under the gravity field of the asteroid. For a small asteroid, the asteroid gravity is negligible, and a trajectory planning method is proposed based on elliptic cavity virtual potential field. The self-organizing control strategy for the follower spacecraft is developed based on a mechanism of velocity planning and velocity tracking. The simulation results show that the self-organizing control strategy is valid for both massive asteroid and small asteroid, and the exploration swarm forms a stable configuration.

Energy Balance Protocol for Wireless Sensor Networks Based on Simulation Potential Field

An energy balance protocol for wireless sensor networks based on simulation potential field has been proposed to address disadvantages of existing sensor network such as it takes inadequate consideration of residual node energy and is to the disadvantage of improvement of network service life and reduction of networking cost. Firstly, studies have been conducted on structure and model of wireless video sensor network to figure out its network structure, energy consumption model and perceptual model; secondly, cluster head selection has been conducted from the perspective of energy consumption balance based on abovementioned models in order to improve network service life effectively. Sensing direction of sensor nodes has also been adjusted with utilization of virtual potential field in order to enlarge coverage range of sensor nodes and to reduce networking cost; finally, it has been proved by comparing simulation experiment regarding the algorithm that the proposed protocol can improve network service life and signal coverage rate of video monitoring area efficiently.

Processing of Deployment Using an Adaptive Self-Spreading Algorithm Based on Electrostatic Field for Mobile Sensor

The deployment of mobile sensor networks is a hotspot issue. This paper is dedicated to proposing a distributed, adaptive, and scalable mobile sensor network algorithm based on the theory in electrostatic field. In the algorithm, the obstacles and nodes in the deployment region were regarded as the charged particles, which were driven by the Coulomb Force exerted by the other particles and obstacles, and eventually all the nodes were distributed throughout the entire network while repelled by the obstacles and other nodes simultaneously. Based on the classical virtual potential field algorithm, the boundary conditions, the static equilibrium conditions and the controllable coverage rate were expanded in the present algorithm, which are also the primary innovation points and contributions of this paper. The efficiency of the proposed algorithm was evaluated by performing simulations under four frequently-used scenarios, namely, deployment under normal conditions, deployment with obstacles, re-deployment due to unpredicted node failures, and deployment with regions of interest. Moreover, the performance of the algorithm was assessed using coverage and uniformity as the criteria. The simulation results indicate that the algorithm runs well under all these four frequently-used scenarios. In a completely unknown deployment area, the designated goal can also be achieved using the proposed algorithm owing to its adaptivity.

A system for application development using aerial robots

Autonomous airborne systems have generated a lot of interest in civilian, as well as military applications. The application development process for such systems is inherently expensive and is prone to costly errors. The majority of the developed applications involve routing and navigation toward targets coupled with obstacle avoidance. In this paper, we present the approach and algorithms that were employed to tackle the routing and avoidance problems. The proposed solutions were applied to land-based robots as well as a quad-rotor aerial system. The quad-rotor flight path navigation and routing was programmed based on GPS and on-board measurement data. Obstacle avoidance was implemented based on an algorithm that relies on the idea of virtual potential field. Kalman filters were implemented to improve the accuracy of the measured data. 3D visualisation was used to visually identify obstacles. In the case of in-building reconnaissance, where GPS signals are very weak and largely useless, data from laser sensors and proximity feeds was aggregated and processed to identify obstacles and the topology of the surrounding environment. The organisation and interaction of these various modules is described in detail.

English

Each application have different Qos (quality of service) in same platform on wireless sensor network. We are proposing coldspots technique and multi path relay algorithm using coldspots technique. It improve the data fidelity and end to end delay of the sensitive to overcome problems like delay minimization and high data integrity and data fidelity. By applying a virtual hybrid potential field IDDR separates packets based on their weight.And the packets are forwarded to the destination through different path applications.Data fidelity can be improve by collecting idle buffer space or under loaded paths to cache excessive packets.For prioritizing packets transmission we are using lyapunov drift technique. IDDR also provide good energy efficiency and scalability.

Dynamic Routing for Data Integrity and Delay Differentiated Services in Wireless Sensor Networks

Applications running on the same Wireless Sensor Network (WSN) platform usually have different Quality of Service (QoS) requirements. Two basic requirements are low delay and high data integrity. However, in most situations, these two requirements cannot be satisfied simultaneously. In this paper, based on the concept of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">potential</i> in physics, we propose IDDR, a multi-path dynamic routing algorithm, to resolve this conflict. By constructing a virtual hybrid potential field, IDDR separates packets of applications with different QoS requirements according to the weight assigned to each packet, and routes them towards the sink through different paths to improve the data fidelity for integrity-sensitive applications as well as reduce the end-to-end delay for delay-sensitive ones. Using the Lyapunov drift technique, we prove that IDDR is stable. Simulation results demonstrate that IDDR provides data integrity and delay differentiated services.

A kind of novel VPF‐based energy‐balanced routing strategy for wireless mesh network

SummaryWireless mesh network (WMN) can sense information and realize end‐network transmission. It consists of numerous wireless sensors, the energy and communication ability of which are limited. A kind of novel VPF‐based energy‐balanced routing strategy for WMN has been presented in this paper. Most of the existing energy‐efficient routing strategy always forwards packets along the minimum energy path to the sink to merely minimize energy consumption, which causes an unbalanced distribution of residual energy among sensor nodes, and eventually results in a network partition. We design the energy‐balanced routing strategy by setting up a mixed virtual potential field in terms of depth and energy by using the physical potential concept. The strategy can force packets to move toward the sink through the dense energy area and protect the nodes, which has relatively low residual energy. By comparing to the other energy‐efficient routing strategy in our designed scenarios, the experimental results show that energy balance and throughput can be improved. Copyright © 2014 John Wiley &amp; Sons, Ltd.

Optimization of the Virtual Potential Field Based on Coverage-Enhancing Algorithm for Directional Sensor Networks

After directional sensor nodes are randomly thrown into target area, coverage ratio often less than the anticipant value, in order to improve the coverage, sensor nodes should turn from overlapping regions to coverage holes by a much faster way. In this paper, we improved the existing potential field based coverage-enhancing algorithm (PFCEA), presented a optimization of the virtual potential field based on coverage-enhancing algorithm for directional sensor networks (OPFCEA), we introducing a new-style virtual node to enhance the coverage of boundary region and a new-style control for the rotation angle. By these ways, we can improve network’s performance. This algorithm enhanced the coverage ratio of the network, the simulation results show the effectiveness of the algorithm.

Optimization Coverage of Wireless Sensor Networks Based on Energy Saving

The separate situation of research has area coverage or target coverage in wireless sensor networks. Based on directional sensing model the algorithm used the virtual potential field to make the sensor nodes shift positions and change directions automatically in monitoring area, With the completion of multiple prior coverage of hot targets which needed higher quality requirements the algorithm could maximize the coverage rate throughout the monitoring area Simulation experiments show that the algorithm has a good ability of selforganizing. It can satisfy the requirements of coverage quality of the hot targets and the whole monitoring area and save resources effectively of the network.