Bibhya N. Sharma

Formation control of a swarm of mobile manipulators

This paper presents a new Lyapunov-based decentralized formation control planner for a swarm of 2-link mobile manipulators in an a priori known environment. To ensure a significant degree of formation stiffness along the flight-path, information on moving ghost targets, inter-robot bounds for aggregation and heading for the mobile manipulators are captured in the control planner. The final desired orientation of the formation is by observing a minimum distance between every member of the swarm and ghost walls. The nonlinear control laws extracted from the Lyapunov-based control scheme are utilized to obtain collision-free trajectories of the swarm in a low-degree formation, whilst ensuring stability of the kinodynamic system governing the swarm. The effectiveness of the controllers is demonstrated by simulating interesting situations.

Lyapunov-based nonlinear controllers for obstacle avoidance with a planar n-link doubly nonholonomic manipulator

A mobile manipulator is a robotic system made up of two components; a mobile platform and a manipulator mounted on the platform equipped with non-deformable wheels. Such a combined system requires complex design and control. This paper considers the autonomous navigation problem of a nonholonomic mobile platform and an n-link nonholonomic manipulator fixed to the platform. For this planar n-link doubly nonholonomic manipulator, we present the first ever set of nonlinear continuous controllers for obstacle avoidance. The controllers provide a collision-free trajectory within a constrained workspace cluttered with fixed obstacles of different shapes and sizes whilst satisfying the nonholonomic and kinodynamic constraints associated with the robotic system. An advantage of the proposed method is the ease at which the acceleration-based control laws can be derived from the Lyapunov function. The effectiveness of the nonholonomic planner is demonstrated via computer simulations.

A new stabilizing solution for motion planning and control of multiple robots

This paper formulates a new scalable algorithm for motion planning and control of multiple point-mass robots. These autonomous robots are designated to move safely to their goals in a priori known workspace cluttered with fixed and moving obstacles of arbitrary positions and sizes. The control laws proposed for obstacle and collision avoidance and target convergence ensure that the equilibrium point of the given system is asymptotically stable. Computer simulations with the proposed technique and applications to a team of two planar (RP) manipulators working together in a common workspace are presented. Also, the robustness of the system in the presence of noise is verified through simulations.

Motion planning and posture control of multiple n -link doubly nonholonomic manipulators

The paper considers the problem of motion planning and posture control of multiple n-link doubly nonholonomic mobile manipulators in an obstacle-cluttered and bounded workspace. The workspace is constrained with the existence of an arbitrary number of fixed obstacles (disks, rods and curves), artificial obstacles and moving obstacles. The coordination of multiple n-link doubly nonholonomic mobile manipulators subjected to such constraints becomes therefore a challenging navigational and steering problem that few papers have considered in the past. Our approach to developing the controllers, which are novel decentralized nonlinear acceleration controllers, is based on a Lyapunov control scheme that is not only intuitively understandable but also allows simple but rigorous development of the controllers. Via the scheme, we showed that the avoidance of all types of obstacles was possible, that the manipulators could reach a neighborhood of their goal and that their final orientation approximated the desired orientation. Computer simulations illustrate these results. KEYWORDS: Lyapunov-based control scheme; Doubly nonholonomic manipulators; Ghost parking bays; Minimum distance technique; Stability; Kinodynamic constraints.

A -Strategy: Facilitating Dual-Formation Control of a Virtually Connected Team

This paper describes the design of new centralized acceleration-based controllers for the multitask problem of motion planning and control of a coordinated lead-carrier team fixed in a dual-formation within an obstacle-ridden environment. A -strategy, where and are Euclidean measures with respect to the lead robot, is developed to ensure virtual connectivity of the carrier robots to the lead robot. This connectivity, built into the system itself, inherently ensures globally rigid formation between each lead-carrier pair of the team. Moreover, a combination of target configuration, -strategy, orientation consensus, and avoidance of end-effector of robots results in a second, locally rigid formation (not infinitesimally rigid). Therefore, for the first time, a dual-formation control problem of a lead-carrier team of mobile manipulators is considered. This and other kinodynamic constraints have been treated simultaneously via the overarching Lyapunov-based control scheme, essentially a potential field method favored in the field of robotics. The formulation of this new scheme, demonstrated effectively via computer simulations, is timely, given that the current proposed engineering solutions, allowing autonomous vehicles on public roads, include the development of special lanes imbued with special sensors and wireless technologies.

Cooperative Control of Multi-robot Systems with a Low-Degree Formation

The utilization of team of robots working in a cooperative manner has huge benefits in moving large payloads. To perform such tasks, a multi robot structure or formation is necessary to coordinate the motions of the robots in a well planned manner. In this paper, the formation control problem of multi car-like mobile robots have been studied. The purpose is to get a swarm of mobile robots in a certain formation pattern to track a desired trajectory to accomplish a set objective. A set of artificial potential field functions is proposed using the Direct Method of Lyapunov for avoiding inter-robot, inter-formation and obstacle collisions and attraction to their designated targets. The effectiveness of the proposed nonlinear acceleration control laws is demonstrated through computer simulation results which prove the efficiency of our control technique and also demonstrates scalability for a large group of robots.

A solution to the motion planning and control problem of a car-like robot via a single-layer perceptron

This paper tackles the problem of motion planning and control of a car-like robot in an obstacle-ridden workspace. A kinematic model of the vehicle, governed by a homogeneous system of first-order differential equations, is used. A solution to the multi-tasking problem of target convergence, obstacle avoidance, and posture control is then proposed. The approach of solving the problem is two-fold. Firstly, a novel velocity algorithm is proposed to drive the car-like robot from its initial position to the target position. Secondly, a single layer artificial neural network is trained to avoid disc-shaped obstacles and provide corresponding weights, which are then used to develop a function for the steering angles. Thus, our method does not need a priori knowledge of the environment except for the goal position. With the help of the Direct Method of Lyapunov, it is shown that the proposed forms of the velocity and steering angle ensure point stability. For posture stability, we model the two parallel boundaries of a row-structured parking bay as continua of disk-shaped obstacles. Thus, our method is extendable to ensuring posture stability, which gives the desired final orientation. Computer simulations of the generated path are presented to illustrate the effectiveness of the method.

Lyapunov-Based Control for a Swarm of Planar Nonholonomic Vehicles

In this paper, we develop a planar Lagrangian swarm model using the Direct Method of Lyapunov to construct the instantaneous velocity of each individual in the swarm. The velocity controllers ensure the cohesion and therefore the stability of the swarm. We introduce novel Lyapunov functions which allow the swarm to navigate in obstacle-free and obstacle-cluttered environments. We apply the methodology to a swarm of planar nonholonomic vehicles. Via computer simulations, we illustrate several self-organizations such as parallel formation, emergent leader, split/rejoin maneuver, and tunnelling for obstacle avoidance.

Science Teachers Accelerated Programme Model: A Joint Partnership in the Pacific Region.

ABSTRACT The paper heralds a new pedagogical model known as the Science Teachers Accelerated Programme as a platform to upgrade the qualifications of secondary school science teachers throughout the Pacific region. Based on a tripartite partnership between a higher education provider, a regional government and a cohort of science teachers, the model offers an accelerated Bachelor’s degree programme to the cohort. Using this tripartite partnership model, a pilot of the Science Teachers Accelerated Programme is underway between the University of the South Pacific, the Government of Samoa and a cohort of science teachers in Samoa. The underpinning activities garnering social and academic integration are highlighted with analytics. The strengths, challenges and opportunities of the new, cohort-taught science model are presented with relevant diagnoses, interventions and adaptive works carried out in the first half of the delivery plan. While the Government of Samoa is considering the implementation of a second cycle, the University of the South Pacific is considering extending the model to other regional countries.

Lyapunov functions for a planar swarm model with application to nonholonomic planar vehicles

This research presents a Lagrangian swarm model for the control of a planar swarm model that has a target. The Direct Method of Lyapunov is used to ensure cohesion of the swarm and stability at the target point. The model proposed can address obstacle-free and obstacle-cluttered environments. Emergent patterns such as split/rejoin, tunnelling maneuver and emergent leader are some of the achievable results, which we apply to nonholonomic planar vehicles.