Simulation Platform for Autonomous Aerial Manipulation in Dynamic Environments

Contact-based aerial interaction control in unknown environments is a challenging issue. To solve this problem, this paper presents an image-based impedance control scheme for an aerial manipulator. Unlike points and image moments, the line features considered in this paper cannot uniquely determine the pose of the onboard camera. Therefore, a nonlinear observer is proposed to online provide supplementary 3D information of the system. After that, a hierarchical tracking controller, which is equipped with an image-space impedance filter, is designed to implement a trajectory tracking task with tunable compliance, while at the same time achieving a subtask that aims to determine the final pose of the aerial manipulator. By planning task-space trajectories, desired interaction behavior can be specified without relying on the global position of the system. Furthermore, the effectiveness criterion of the observer is derived, and the stability of the system is proven. Several experiments, including a push-and-slide task, robustness analysis, and a comparison with the state of the art have been conducted to demonstrate the feasibility of the method. Note to Practitioners—This article presents a method for controlling an aerial manipulator to interact with unknown environments without measuring the global position of both the environment and the aerial manipulator. Furthermore, unlike the existing methods, the proposed visual servoing method is based on line features, which are generally more robust than point features. Moreover, it would be intuitive for users to specify the approaching path and the interaction behavior of the aerial manipulator by just planning the image feature trajectories and the desired distance between the aerial manipulator and the environment. This distance is online estimated using the visual feedback of a monocular camera, instead of relying on any costly 3D-vision sensors or lidars, making it an economical solution for aerial manipulation in field environments.

<p>Traditional aerial manipulation systems were usually composed of rigid-link manipulators attached to an aerial platform, arising several rigidity-related issues such as difficulties of reach, compliant motion, adaptability to object’s shape and pose uncertainties, and safety of human-manipulator interactions, especially in unstructured and confined environments. To address these issues, partially compliant manipulators, composed of rigid links and compliant/flexible joints, were proposed; however, they still suffer from insufficient dexterity and maneuverability. In this article, a new set of compliant aerial manipulators is suggested. For this purpose, the concept of aerial continuum manipulation system (ACMS) is introduced, several conceptual configurations are proposed, and the functionalities of ACMSs for different applications are discussed. Then, the performances of proposed aerial manipulators are compared with conventional aerial manipulators by implementing available benchmarks in the literature. To enhance the comparison, new features with related benchmarks are presented and used for evaluation purposes. In this study, the advantages of ACMSs over their rigid-link counterparts are illustrated and the potential applications of ACMSs are suggested. The open problems such as those related to dynamic coupling and control of ACMSs are also highlighted.</p>

Unmanned aerial vehicles (UAVs), when paired with an onboard camera, have proven to be useful tools in many applications, including aerial photography, precision agriculture, and search and rescue operations. Likewise, UAVs capable of physically interacting with the environment have shown great potential to help people perform dangerous, or time-consuming tasks more safely and efficiently than they could on their own. However, due to onboard computation and battery life limitations and complex flight dynamics, using UAVs to physically interact with the environment is still a developing area of research. Considering these limitations, the primary goals of this work are to (1) develop a new UAV platform for aerial manipulation, (2) develop modular hardware and software for the platform to enable specific tasks to be performed autonomously, and (3) develop a visual target tracking method to enable robust performance of autonomous aerial manipulation tasks in unstructured, real-world environments. To that end, the design of the Interacting-BoomCopter UAV (I-BC) is presented here as a new platform for aerial manipulation. With a simple tricopter frame, a single additional actuator for generating horizontal forces, and lightweight, modular end-effectors, the I-BC aims to balance efficiency and functionality in performing aerial manipulation tasks, and is able to perform various tasks such as mounting sensors in hard-to-reach places, and opening small doors or panels. An onboard camera, force and distance sensors, and a powerful single board computer (SBC) enable the I-BC to operate autonomously in unstructured environments, with potential applications in areas such as large-scale infrastructure inspection, industrial inspection and maintenance, and nuclear decontamination efforts.

Lack of electricity in remote areas has become a challenge to be solved in order to improve the welfare of people living there. The improvement of technologies based in renewable energy sources (RES) in recent years has contributed to the electrification of remote areas. Traditional fossil fuel generators have given way to micro-grids based on RES, which have been proved to be very competitive solutions. Hybrid DC/AC micro-grids are very common solutions for off-grid power infrastructures in remote or rural areas. Furthermore, it seems to be that hybrid DC/AC systems will be part of the future grid solutions due to their efficiency. This paper proposes a modular simulation platform to test such systems. The micro-grid implemented for the analyzed simulation consists on a photovoltaic array, energy storage system based on batteries and a DC load tied to the DC side whereas just an AC load is tied to the AC side. The simulation results with changing solar radiation conditions and different load requirements are presented and explained to observe that the implemented system is stable.

In the process of development of numerical control system, we would actually go to the processing plant to test a strategy or compare the accuracy of trajectory planning, which is not only inefficient, but may lead to mechanical platform damage or safety incidents due to improper use of the parameters. Therefore, we aim to establish virtual simulation system for the lead screw guide system. Based on the process of CNC machining process, a whole architecture of virtual simulation platform is put forward. Virtual simulation platform can be divided into specific modules, including trajectory planning module» control module, single axis platform module, error analysis module and compensation module. We analyze the mathematical modeling based on a XY table. In order to reflect the characteristics of the system, we mainly focus on the reverse gap, friction force and other nonlinear factors analysis and modeling. We establish the model of a servo drive and mechanical structure. Finally, based on the simulation platform, we add the compensation control module to the virtual simulation system. By comparing contour error of experimental platform and simulation platform before and after compensation, we prove that the compensation is effective.

Mechanical Bus for Modular Product Design

This paper introduces a novel and general real-time adaptive motion planning (RAMP) approach suitable for planning trajectories of high-DOF or redundant robots, such as mobile manipulators, in dynamic environments with moving obstacles of unknown trajectories. The RAMP approach enables simultaneous path and trajectory planning and simultaneous planning and execution of motion in real time. It facilitates real-time optimization of trajectories under various optimization criteria, such as minimizing energy and time and maximizing manipulability. It also accommodates partially specified task goals of robots easily. The approach exploits redundancy in redundant robots (such as locomotion versus manipulation in a mobile manipulator) through loose coupling of robot configuration variables to best achieve obstacle avoidance and optimization objectives. The RAMP approach has been implemented and tested in simulation over a diverse set of task environments, including environments with multiple mobile manipulators. The results (and also the accompanying video) show that the RAMP planner, with its high efficiency and flexibility, not only handles a single mobile manipulator well in dynamic environments with various obstacles of unknown motions in addition to static obstacles, but can also readily and effectively plan motions for each mobile manipulator in an environment shared by multiple mobile manipulators and other moving obstacles.

This paper is concerned with the motion control problem of an aerial manipulator that consists of a quadrotor base and a manipulator. We propose a novel control strategy that incorporates a simplified model considering the critical dynamics, and a linear-MPC-based trajectory converter to ensure precise velocity tracking for the end-effector. The proposed method is a full-body control approach that coordinates both the quadrotor base and the manipulator, ensuring seamless motion execution across the entire system. Furthermore, the method requires only a small set of dynamic model parameters, making it easy to deploy in practice. The method is validated through motion response experiments on a custom-designed aerial manipulator platform. Experimental results show that the platform performs well in outdoor environments, and the control strategy effectively suppresses angular velocity disturbances while coordinating the full-body joints for end-effector motion tasks.

In the recent years, wireless sensor networks have attracted a lot of attention due to their broad application areas. In many application scenarios, hundreds or thousands of sensor nodes may be deployed in the physical environment. To design, implement, manage and maintain such large-scale networks efficiently is a major challenge which requires an integrated middleware development approach. In this paper, we focus on the development of a simulation platform specifically designed to support the development of sensor network middleware services. This novel platform is designed in a modular manner to facilitate the rapid integration and testing of different middleware algorithms and services. We present the simulator's software architecture and its operation. A case study to illustrate the usage of our simulation platform is also presented. The simulation platform shows potentials to support the research and development of middleware servicesfor wireless sensor networks.

Chapter 21 - Event-driven programming-based path planning and navigation of UAVs around a complex urban environment

Active suspension designs rely on knowledge of system parameters such as vehicle mass to achieve their objectives of improved passenger comfort and road handling. Previously, we proposed a novel nonlinear design methodology for active suspensions, which uses a nonlinear control objective to explicitly incorporate rattlespace travel limits and prevent the suspension from hitting them. We have also shown that this scheme is quite robust to uncertainty in most system parameters, and that adaptation can be used to deal with the parameters to which the scheme is not robust. In our previous adaptive design, we used a tuning-functions-based adaptation scheme. In this paper, we use an alternative modular procedure to design an adaptive nonlinear controller for active suspension systems. In the modular approach, the controller and identifier modules are designed separately; hence the designer has much more flexibility in the choice of update laws compared to the tuning functions design. Hence, we employ several different identifiers, including passive and swapping schemes, in our modular design. Our simulation results show that the modular design results in closed-loop performance similar to that of the tuning functions design.

A new hardware platform for digital real-time simulation and control applications is introduced which is highly expandable and customizable due to its modular design and flexible, open interfaces. The system is based on digital signal processors (DSPs) and field programmable gate arrays (FPGAs). A detailed description of the processor and interface boards as core components of the system is given. A small-scale desktop system for hardware-in-the-loop real-time simulations is shown. Furthermore, modeling methodologies and commonly used integration techniques with regard to usual problems and practical implementation are presented. An actual implementation is presented as an example simulation which is used to verify the functionality and evaluate the performance of the real-time simulation platform. A real-time simulation of a buck converter with a time-step of 1 µs without FPGA co-processing is shown and the simulation results are compared to real hardware measurements. To address the common problem of inter time-step switching, solutions are discussed and two approaches are implemented and compared. In total, this paper presents a short overview of digital real-time simulation including modeling and integration, software implementation, hardware platform for code execution and hardware-in-the-loop testing.

Mobile manipulation targets applications in dynamic and unstructured environments. Motion generation methods suitable for these applications must account for end-effector task constraints, must reason about environment uncertainty, i.e. the fact that the exact state of the dynamic environment cannot be known to the robot, and should do so only using their on-board sensors. We present the Expected-Shortest-Path Elastic Roadmap (ESPER) planner as a motion generation method suitable for mobile manipulation. It integrates task-constrained, whole-body, reactive motion generation in high-dimensional configuration space with reasoning about uncertainty. In our experiments, we generate task-consistent motion in uncertain environments on a real-world mobile manipulator only relying on on-board sensors.

Modular neural dynamic surface control for position tracking of permanent magnet synchronous motor subject to unknown uncertainties

For aerial manipulators, a steady flight must be guaranteed to perform safe interaction with the surrounding environment. This paper focuses on the development of a position control algorithm for an aerial manipulator system (AMS). The position control algorithm is based on the Immersion and Invariance (I&I) theory. The proposed controller maintains the position of the aerial manipulator at the desired point under external and internal disturbances. The control architecture uses a Visual-SLAM technique using on-board sensors for AMS positioning. A series of outdoor experimental tests are performed to demonstrate the effectiveness of the proposed control strategy.