In this paper, the problem of coordinated transportation of heavy payload by a team of UAVs in a cluttered environment is addressed. The payload is modeled as a rigid body and is assumed to track a pre-computed global flight trajectory from a start point to a goal point. Due to the presence of local dynamic obstacles in the environment, the UAVs must ensure that there is no collision between the payload and these obstacles while ensuring that the payload oscillations are kept minimum. An Integrated Decision Controller (IDC) is proposed, that integrates the optimal tracking control law given by a centralized Model Predictive Controller with safety-critical constraints provided by the Exponential Control Barrier Functions. The entire payload-UAV system is enclosed by a safe convex hull boundary, and the IDC ensures that no obstacle enters this boundary. To evaluate the performance of the IDC, the results for a numerical simulation as well as a high-fidelity Gazebo simulation are presented. An ablation study is conducted to analyze the robustness of the proposed IDC against practical dubieties like noisy state values, relative obstacle safety margin, and payload mass uncertainty. The results clearly show that the IDC achieves both trajectory tracking and obstacle avoidance successfully while restricting the payload oscillations within a safe limit.
OA-ECBVC: A Cooperative Collision-free Encirclement and Capture Approach in Cluttered Environments
The Chinese University of Hong Kong（香港中文大学）；The University of Hong Kong（香港大学）；Hebei University of Science and Technology（河北科技大学）；Tongji University（同济大学）
Cooperative Transportation using Multiple Single-Rotor Robots and Decentralized Control for Unknown Payloads
Cloud Informatics Research-Domain, Toyota Central R&D Labs., Inc.（丰田中央研究实验室云信息研究部门）；R-Frontier Division, Frontier Research Center. Toyota Motor Corporation（丰田电机公司前沿研究中心R前沿部门）
Cooperative Payload Estimation by a Team of Mocobots
Department of Mechanical Engineering, Center for Robotics and Biosystems, Northwestern University（机械工程系、机器人与生物系统中心、西北大学）；Center for Robotics and Biosystems, Department of Electrical and Computer Engineering, Northwestern Institute on Complex Systems, Northwestern University（机器人与生物系统中心、电气与计算机工程系、复杂系统研究所、西北大学）；Department of Mechanical Engineering, Center for Robotics and Biosystems, Northwestern Institute on Complex Systems, Northwestern University（机械工程系、机器人与生物系统中心、复杂系统研究所、西北大学）
A Cooperative Aerial System of A Payload Drone Equipped with Dexterous Rappelling End Droid for Cluttered Space Pickup
School of Aerospace Science and Engineering, Beihang University（北京航空航天大学航空航天科学与工程学院）；Hangzhou International Innovation Institute of Beihang University（北京航空航天大学杭州国际创新研究院）；Institute of Unmanned System, Beihang University（北京航空航天大学无人系统研究院）；Tianmushan Laboratory（天门山实验室）
This paper addresses the problem of cooperative transport of a point mass hoisted by two aerial robots. Treating the robots as a leader and a follower, the follower stabilizes the system with respect to the leader using only feedback from its Inertial Measurement Units (IMU). This is accomplished by neglecting the acceleration of the leader, analyzing the system through the generalized coordinates or the cables' angles, and employing an observation model based on the IMU measurements. A lightweight estimator based on an Extended Kalman Filter (EKF) and a controller are derived to stabilize the…
National Yang Ming Chiao Tung University（台湾阳明交通大学）
A tracking controller for unmanned aerial vehicles (UAVs) is developed to track moving targets undergoing unknown translational and rotational motions. The main challenges are to control both the relative positions and angles between the target and the UAVs to within desired values, and to guarantee that the generated control inputs to the UAVs are feasible (i.e., within their motion capabilities). Moreover, the UAVs are controlled to ensure that the target always remains within the fields of view of their onboard cameras. To the best of our knowledge, this is the first work to apply multiple …
Drones Guiding Drones: Cooperative Navigation of a Less-Equipped Micro Aerial Vehicle in Cluttered Environments
Multi-robot Systems Group, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague（多机器人系统组，控制系，电气工程系，捷克技术大学）
Recently, there have been numerous advances in the development of biologically inspired lightweight Micro Aerial Vehicles (MAVs). While autonomous navigation is fairly straight-forward for large UAVs as expensive sensors and monitoring devices can be employed, robust methods for obstacle avoidance remains a challenging task for MAVs which operate at low altitude in cluttered unstructured environments. Due to payload and power constraints, it is necessary for such systems to have autonomous navigation and flight capabilities using mostly passive sensors such as cameras. In this paper, we descri…
PAINT: Partner-Agnostic Intent-Aware Cooperative Transport with Legged Robots
Robotic Systems Lab, ETH Zurich, Switzerland（瑞士苏黎世联邦理工学院机器人系统实验室）；Computational Robotics Lab, ETH Zurich, Switzerland（瑞士苏黎世联邦理工学院计算机器人学实验室）；ETH AI Center, ETH Zurich, Switzerland（瑞士苏黎世联邦理工学院ETH人工智能中心）
New York University（纽约大学）；New York University Abu Dhabi（纽约大学阿布扎比分校）
The control problem of a multi-copter swarm, mechanically coupled through a modular lattice structure of connecting rods, is considered in this article. The system's structural elasticity is considered in deriving the system's dynamics. The devised controller is robust against the induced flexibilities, while an inherent adaptation scheme allows for the control of asymmetrical configurations and the transportation of unknown payloads. Certain optimization metrics are introduced for solving the individual agent thrust allocation problem while achieving maximum system flight time, resulting in a…
Cooperative Control of Multi-Quadrotors for Transporting Cable-Suspended Payloads: Obstacle-Aware Planning and Event-Based Nonlinear Model Predictive Control
Toronto Metropolitan University（多伦多都会大学）；University of Alberta（阿尔伯塔大学）
Cooperative Modular Manipulation with Numerous Cable-Driven Robots for Assistive Construction and Gap Crossing
University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；US Army Corps of Engineers Construction Engineering Research Laboratory（美国陆军工兵团建筑工程研究实验室）；Istituto Italiano di Tecnologia (IIT)（意大利技术研究院）；Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校机械科学与工程学院）
Trajectory Planning for a Multi-UAV Rigid-Payload Cascaded Transportation System Based on Enhanced Tube-RRT*
School of Aerospace Science and Technology, Beijing Institute of Technology（航天科学与技术学院，北京理工大学）；Graduate School of Systems and Information Engineering, University of Tsukuba（系统与信息工程研究生院，筑波大学）
Low-Complexity Cooperative Payload Transportation for Nonholonomic Mobile Robots Under Scalable Constraints
School of Mechanical Electrical Engineering and Automation, Harbin Institute of Technology Shenzhen（哈尔滨工业大学（深圳）机电工程与自动化学院）；School of Control Science and Engineering, Shandong University（山东大学控制科学与工程学院）；School of Automation and Intelligent Manufacturing, Southern University of Science and Technology（南方科技大学自动化与智能制造学院）
IIIT Hyderabad（国际信息技术研究所海得拉巴分校）；University of Genoa（热那亚大学）；University of Tübingen（图宾根大学）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；IIT Jodhpur（焦特布尔印度理工学院）
In this paper, a kinematic motion planning algorithm for cooperative spatial payload manipulation is presented. A hierarchical approach is introduced to compute real-time collision-free motion plans for a formation of mobile manipulator robots. Initially, collision-free configurations of a deformable 2-D virtual bounding box are identified, over a planning horizon, to define a convex workspace for the entire system. Then, 3-D payload configurations whose projections lie within the defined convex workspace are computed. Finally, a convex decentralized model-predictive controller is formulated t…
Dual-Quadruped Collaborative Transportation in Narrow Environments via Safe Reinforcement Learning
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Advanced Remanufacturing & Technology Centre (ARTC)（先进再制造与技术中心）；Agency for Science, Technology and Research (A*STAR)（科技研究局）；Cheng Kar-Shun Robotics Institute, The Hong Kong University of Science and Technology（陈克舜机器人研究所，香港科技大学）
Self-Organizing Aerial Swarm Robotics for Resilient Load Transportation : A Table-Mechanics-Inspired Approach
School of Automation Science and Electrical Engineering, Beihang University（北京航空航天大学自动化科学与电气工程学院）；Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong（香港中文大学机械与自动化工程系）
HetSwarm: Cooperative Navigation of Heterogeneous Swarm in Dynamic and Dense Environments through Impedance-based Guidance
Intelligent Space Robotics Laboratory, Center for Digital Engineering, Skolkovo Institute of Science and Technology（斯克尔科夫科学与技术研究所智能空间机器人实验室，数字工程中心）；Multi-Robot Autonomy Laboratory, Department of Data Science and Engineering, IISER Bhopal（IISER博帕尔数据科学与工程系多机器人自主性实验室）
A leader-follower system is developed for cooperative transportation. To the best of our knowledge, this is the first work that inter-UAV communication is not required and the reference trajectory of the payload can be modified in real time, so that it can be applied to a dynamically changing environment. To track the modified reference trajectory in real time under the communication-free condition, the leader-follower system is considered as a nonholonomic system in which a controller is developed for the leader to achieve asymptotic tracking of the payload. To eliminate the need to install f…
This paper addresses the problem of cooperative object transportation for multiple Underwater Vehicle Manipulator Systems (UVMSs) in a constrained workspace involving static obstacles. We propose a Nonlinear Model Predictive Control (NMPC) approach for a team of UVMSs in order to transport an object while avoiding significant constraints and limitations such as: kinematic and representation singularities, obstacles within the workspace, joint limits and control input saturations. More precisely, by exploiting the coupled dynamics between the robots and the object, and using certain load sharin…
Australian Centre for Robotic Vision (ACRV)（澳大利亚机器人视觉中心（ACRV））；Queensland University of Technology (QUT)（昆士兰科技大学（QUT））；University of Adelaide（阿德莱德大学）；Australian National University (ANU)（澳大利亚国立大学（ANU））
Robotic manipulation and grasping in cluttered and unstructured environments is a current challenge for robotics. Enabling robots to operate in these challenging environments have direct applications from automating warehouses to harvesting fruit in agriculture. One of the main challenges associated with these difficult robotic manipulation tasks is the motion planning and control problem for multi-DoF (Degree of Freedom) manipulators. This paper presents the design and performance evaluation of a low-cost Cartesian manipulator, Cartman who took first place in the Amazon Robotics Challenge 201…
This paper addresses the problem of cooperative object transportation for multiple Underwater Vehicle Manipulator Systems (UVMSs) in a constrained workspace with static obstacles, where the coordination relies solely on implicit communication arising from the physical interaction of the robots with the commonly grasped object. We propose a novel distributed leader-follower architecture, where the leading UVMS, which has knowledge of the object's desired trajectory, tries to achieve the desired tracking behavior via an impedance control law, navigating in this way, the overall formation towards…
CARE: Consistent Action-Response Execution for Human-Guided Robot Transport
School of Engineering, The University of Western Australia（西澳大学工程学院）；Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong（香港中文大学机械与自动化工程系）；School of Electrical Engineering and Computer Science, The University of Queensland（昆士兰大学电气工程与计算机科学学院）
Queensland University of Technology（昆士兰科技大学）；Data61 / CSIRO（Data61 / 联邦科学与工业研究组织）；Griffith University（格里菲斯大学）
The use of multi-rotor Unmanned Aerial Vehicles (UAVs) for search and rescue as well as remote sensing is rapidly increasing. Multi-rotor UAVs, however, have limited endurance. The range of UAV applications can be widened if teams of multiple UAVs are used. We propose a framework for a team of UAVs to cooperatively explore and find a target in complex GPS-denied environments with obstacles. The team of UAVs autonomously navigates, explores, detects, and finds the target in a cluttered environment with a known map. Examples of such environments include indoor scenarios, urban or natural canyons…
Virginia Tech（弗吉尼亚理工大学）；California Institute of Technology（加州理工学院）
This paper presents a layered control approach for real-time trajectory planning and control of robust cooperative locomotion by two holonomically constrained quadrupedal robots. A novel interconnected network of reduced-order models, based on the single rigid body (SRB) dynamics, is developed for trajectory planning purposes. At the higher level of the control architecture, two different model predictive control (MPC) algorithms are proposed to address the optimal control problem of the interconnected SRB dynamics: centralized and distributed MPCs. The distributed MPC assumes two local quadra…
Exploring Unstructured Environments using Minimal Sensing on Cooperative Nano-Drones
Computer Vision and Aerial Robotics Group at Universidad Politécnica de Madrid（马德里理工大学计算机视觉与空中机器人小组）；Centre for Automation and Robotics C.A.R. (UPM-CSIC)（自动化与机器人中心（UPM-CSIC））；Department of Mechanical Engineering, Texas A&M University（机械工程系，德克萨斯A&M大学）
KTH Royal Institute of Technology（KTH皇家理工学院）；School of Electrical Engineering and Computer Science（电气工程与计算机科学学院）
Control and planning of multi-agent systems is an active and increasingly studied topic of research, with many practical applications such as rescue missions, security, surveillance, and transportation. This thesis addresses the planning and control of multi-agent systems under temporal logic tasks. The considered systems concern complex, robotic, manipulator-endowed systems, which can coordinate in order to execute complicated tasks, including object manipulation/transportation. Motivated by real-life scenarios, we take into account high-order dynamics subject to model uncertainties and unkno…
