Formation control of multiple robots using parametric and implicit representations

A novel method is presented for formation control of a group of autonomous mobile robots using parametric and implicit descriptions of the desired formation. Shape formation is controlled by using potential fields generated from Implicit Polynomial (IP) representations and the control for keeping the desired shape is designed using Elliptical Fourier Descriptors (EFD). Coordination of the robots is modeled by linear springs between each robot and its nearest two neighbors. This approach offers more flexibility in the formation shape and scales well to different swarm sizes and to heterogeneous systems. The method is simulated on robot groups with different sizes to form various formation shapes

Coordination of multiple mobile manipulators for ordered sorting of cluttered objects

We present a coordination method for multiple mobile manipulators to sort objects in clutter. We consider the object rearrangement problem in which the objects must be sorted into different groups in a particular order. In clutter, the order constraints could not be easily satisfied since some objects occlude other objects so the occluded ones are not directly accessible to the robots. Those objects occluding others need to be moved more than once to make the occluded objects accessible. Such rearrangement problems fall into the class of nonmonotone rearrangement problems which are computationally intractable. While the nonmonotone problems with order constraints are harder, involving with multiple robots requires another computation for task allocation. The proposed method first finds a sequence of objects to be sorted using a search such that the order constraint in each group is satisfied. The search can solve nonmonotone instances that require temporal relocation of some objects to access the next object to be sorted. Once a complete sorting sequence is found, the objects in the sequence are assigned to multiple mobile manipulators using a greedy allocation method. We develop four versions of the method with different search strategies. In the experiments, we show that our method can find a sorting sequence quickly (e.g., 4.6 sec with 20 objects sorted into five groups) even though the solved instances include hard nonmonotone ones. The extensive tests and the experiments in simulation show the ability of the method to solve the real-world sorting problem using multiple mobile manipulators.Comment: Presented at iROS 202

Sampling-Based Multi-Robot Exploration

International audienceThis paper presents a new approach for collaborative multi-robot planning issues. The main problem that arises from multi-robot exploration is waiting situations. We consider that such problem involves two or more autonomous robots in an unknown environment. The mission objective is to explore the entire map, while trying to minimize its executing time. Moreover if each robot uses the same topological graph, then it uses the same exploration path that makes waiting situations arising. To solve this problem, we propose a new approach in this paper based on sampling iteratively maps to allow interactive multi-robot exploration. Our approach has been implemented in simulation and the experiments demonstrate that the overall completion time of an exploration task can be significantly reduced by our sampling-based method

Formation control of nonholonomic mobile robots using implicit polynomials and elliptic Fourier descriptors

This paper presents a novel method for the formation control of a group of nonholonomic mobile robots using implicit and parametric descriptions of the desired formation shape. The formation control strategy employs implicit polynomial (IP) representations to generate potential fields for achieving the desired formation and the elliptical Fourier descriptors (EFD) to maintain the formation once achieved. Coordination of the robots is modeled by linear springs between each robot and its two nearest neighbors. Advantages of this new method are increased flexibility in the formation shape, scalability to different swarm sizes and easy implementation. The shape formation control is first developed for point particle robots and then extended to nonholonomic mobile robots. Several simulations with robot groups of different sizes are presented to validate our proposed approach

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

Object Isolation With Minimal Impact Towards The Object Of Interest In A Complex Environment Using Manipulation Primitives

It is common in the field of robotic manipulation to specifically target and precisely move, displace or manipulate the targeted object of interest. This however may not always be the best possible course of action as there are situations where it is not possible to manipulate the object of interest or is not in a condition to be manipulated. This research paper explores and subsequently proposes 3 object isolation technique for the purpose of isolating a targeted object of interest from the environment incontras to the standard utilization of object singulation technique. The goal was to develop an algorithm than can successfully isolate the object of interest from the environment via removing the environment without/with minimal impact towards the object of interest. Results from the experiment indicated that the proposed algorithms can successfully isolate the object of interest with minimal impact towards the object of interest scoring an average of 0.85cm/actuation for MSMAPPS, 0.75cm/actuation for MSMAPOS and finally 0.27cm/actuation for BSMAPOS. These results indicates a relatively small displacement per actuation at 4.35% displacement per actuation, 3.75% displacement per actuation, and 1.35% displacement per actuation relative to the workspace respectivel

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics

Efficient Object Isolation In Complex Environment Using Manipulation Primitive On A Vision Based Mobile 6DOF Robotic Arm

This paper explores the idea of manipulation aided- perception in the context of isolating an object of interest from other small objects of varying degree of clusterization in order to obtain high quality training images.The robot utilizes a novel algorithm to plot out the position for each noise objects and its destined position as well as its trajectory and then utilizes manipulation primitives (pushing motion) to move said object along the planned trajectory.The method was demonstrated using Vrep simulation software which simulated a Kuka YouBot fitted with a camera on the gripper.We evaluated our approach by simulating the robot manipulators in an experiment which successfully isolate the object of interest from noise objects with at a rate of 77.46% at an average of 0.56 manipulations per object compared to others at 1.76 manipulations subsequently speeding up the time taken for manipulation from 12.58 minutes to 2.6 minutes however suffers from a tradeoff in terms of accuracy when comparing the similar works to our proposed method

Optimisation-based verification process of obstacle avoidance systems for unmanned vehicles

This thesis deals with safety verification analysis of collision avoidance systems for unmanned vehicles. The safety of the vehicle is dependent on collision avoidance algorithms and associated control laws, and it must be proven that the collision avoidance algorithms and controllers are functioning correctly in all nominal conditions, various failure conditions and in the presence of possible variations in the vehicle and operational environment. The current widely used exhaustive search based approaches are not suitable for safety analysis of autonomous vehicles due to the large number of possible variations and the complexity of algorithms and the systems. To address this topic, a new optimisation-based verification method is developed to verify the safety of collision avoidance systems. The proposed verification method formulates the worst case analysis problem arising the verification of collision avoidance systems into an optimisation problem and employs optimisation algorithms to automatically search the worst cases. Minimum distance to the obstacle during the collision avoidance manoeuvre is defined as the objective function of the optimisation problem, and realistic simulation consisting of the detailed vehicle dynamics, the operational environment, the collision avoidance algorithm and low level control laws is embedded in the optimisation process. This enables the verification process to take into account the parameters variations in the vehicle, the change of the environment, the uncertainties in sensors, and in particular the mismatching between model used for developing the collision avoidance algorithms and the real vehicle. It is shown that the resultant simulation based optimisation problem is non-convex and there might be many local optima. To illustrate and investigate the proposed optimisation based verification process, the potential field method and decision making collision avoidance method are chosen as an obstacle avoidance candidate technique for verification study. Five benchmark case studies are investigated in this thesis: static obstacle avoidance system of a simple unicycle robot, moving obstacle avoidance system for a Pioneer 3DX robot, and a 6 Degrees of Freedom fixed wing Unmanned Aerial Vehicle with static and moving collision avoidance algorithms. It is proven that although a local optimisation method for nonlinear optimisation is quite efficient, it is not able to find the most dangerous situation. Results in this thesis show that, among all the global optimisation methods that have been investigated, the DIviding RECTangle method provides most promising performance for verification of collision avoidance functions in terms of guaranteed capability in searching worst scenarios