In this paper, we present a novel approach to efficiently generate collision-free optimal trajectories for multiple non-holonomic mobile robots in obstacle-rich environments. Our approach first employs a graph-based multi-agent path planner to find an initial discrete solution, and then refines this solution into smooth trajectories using nonlinear optimization. We divide the robot team into small groups and propose a prioritized trajectory optimization method to improve the scalability of the algorithm. Infeasible sub-problems may arise in some scenarios because of the decoupled optimization framework. To handle this problem, a novel grouping and priority assignment strategy is developed to increase the probability of finding feasible trajectories. Compared to the coupled trajectory optimization, the proposed approach reduces the computation time considerably with a small impact on the optimality of the plans. Simulations and hardware experiments verified the effectiveness and superiority of the proposed approach.
This work addresses the problem of kinematic trajectory planning for mobile manipulators with non-holonomic constraints, and holonomic operational-space tracking constraints. We obtain whole-body trajectories and time-varying kinematic feedback controllers by solving a Constrained Sequential Linear Quadratic Optimal Control problem. The employed algorithm features high efficiency through a continuous-time formulation that benefits from adaptive step-size integrators and through linear complexity in the number of integration steps. In a first application example, we solve kinematic trajectory p…
Enhanced $A^{*}$ Algorithm for Mobile Robot Path Planning with Non-Holonomic Constraints
U R Rao Satellite Centre, Indian Space Research Organization (ISRO)（U.R.拉奥卫星中心，印度空间研究组织（ISRO））；Robert Bosch Centre for Cyber Physical Systems, Indian Institute of Science（罗伯特·博世网络物理系统中心，印度科学学院）
We design an model predictive control (MPC) approach for planning and control of non-holonomic mobile robots. Linearizing the system dynamics around the pre-computed reference trajectory gives a time-varying LQ MPC problem. We analytically show that by specially designing the MPC controller, the time-varying, linearized system can yield asymptotic stability around the origin in the tracking task. We further propose two obstacle avoidance methods. We show that by defining linearized constraint in velocity-space and explicitly coupling the two control inputs based on current state, our second me…
Istituto Italiano di Tecnologia（意大利技术研究院）；Università Cattolica del Sacro Cuore（圣心天主教大学）
Mobile manipulators that combine mobility and manipulability, are increasingly being used for various unstructured application scenarios in the field, e.g. vineyards. Therefore, the coordinated motion of the mobile base and manipulator is an essential feature of the overall performance. In this paper, we explore a whole-body motion controller of a robot which is composed of a 2-DoFs non-holonomic wheeled mobile base with a 7-DoFs manipulator (non-holonomic wheeled mobile manipulator, NWMM) This robotic platform is designed to efficiently undertake complex grapevine pruning tasks. In the contro…
We present a batch trajectory optimizer that can simultaneously solve hundreds of different instances of the problem in real-time. We consider holonomic robots but relax the assumption of circular base footprint. Our main algorithmic contributions lie in: (i) improving the computational tractability of the underlying non-convex problem and (ii) leveraging batch computation to mitigate initialization bottlenecks and improve solution quality. We achieve both goals by deriving a multi-convex reformulation of the kinematics and collision avoidance constraints. We exploit these structures through a…
University of California San Diego（加州大学圣地亚哥分校）；Purdue University（普渡大学）
Fast and efficient sampling-based motion planning (SMP) is an integral component of many robotic systems, such as autonomous cars. A popular technique to improve the efficiency of these planners is to restrict search space in the planning domain. Existing algorithms define parametric functions to bound the search space, but these do not extend to non-holonomic robotic systems. Recent learning-based methods use a combination of convolutional and fully connected networks to encode the planning space. However, these methods are restricted to fixed map sizes, which are often not realistic in the r…
Avoiding collisions is one of the vital tasks for systems of autonomous mobile agents. We focus on the problem of finding continuous coordinated paths for multiple mobile disc agents in a 2-d environment with polygonal obstacles. The problem is PSPACE-hard, with the state space growing exponentially in the number of agents. Therefore, the state of the art methods include mainly reactive techniques and sampling-based iterative algorithms. We compare the performance of a widely-used reactive method ORCA with three variants of a popular planning algorithm RRT* applied to multi-agent path planning…
We present a novel class of robots belonging to Constrained Collaborative Mobile Agents (CCMA) family which consists of ground mobile bases with non-holonomic constraints. Moreover, these mobile robots are constrained by closed-loop kinematic chains consisting of revolute joints which can be either passive or actuated. We also describe a novel trajectory optimization method which is general with respect to number of mobile robots, topology of the closed-loop kinematic chains and placement of the actuators at the revolute joints. We also extend the standalone trajectory optimization method to o…
MPC-based motion planning for non-holonomic systems in non-convex domains
University of Applied Sciences Kempten（应用科学大学凯普滕）；Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla（系统与自动化工程系，塞维利亚大学）；CNR-IEIIT（意大利国家研究委员会-IEIIT）
Moscow Institute of Physics and Technology（莫斯科物理技术学院）；Federal Research Center “Computer Science and Control” RAS（俄罗斯科学院“计算机科学与控制”联邦研究中心）
Multi-Agent Path Finding (MAPF) is a long-standing problem in Robotics and Artificial Intelligence in which one needs to find a set of collision-free paths for a group of mobile agents (robots) operating in the shared workspace. Due to its importance, the problem is well-studied and multiple optimal and approximate algorithms are known. However, many of them abstract away from the kinematic constraints and assume that the agents can accelerate/decelerate instantaneously. This complicates the application of the algorithms on the real robots. In this paper, we present a method that mitigates thi…
Ecole Centrale de Lille（里尔中央理工学院）；Beihang University（北京航空航天大学）
A high redundant non-holonomic humanoid mobile dual-arm manipulator system is presented in this paper where the motion planning to realize "human-like" autonomous navigation and manipulation tasks is studied. Firstly, an improved MaxiMin NSGA-II algorithm, which optimizes five objective functions to solve the problems of singularity, redundancy, and coupling between mobile base and manipulator simultaneously, is proposed to design the optimal pose to manipulate the target object. Then, in order to link the initial pose and that optimal pose, an off-line motion planning algorithm is designed. I…
Optimization fabrics are a geometric approach to real-time local motion generation, where motions are designed by the composition of several differential equations that exhibit a desired motion behavior. We generalize this framework to dynamic scenarios and non-holonomic robots and prove that fundamental properties can be conserved. We show that convergence to desired trajectories and avoidance of moving obstacles can be guaranteed using simple construction rules of the components. Additionally, we present the first quantitative comparisons between optimization fabrics and model predictive con…
Collision avoidance in unknown obstacle-cluttered environments may not always be feasible. This paper focuses on an emerging paradigm shift in which potential collisions with the environment can be harnessed instead of being avoided altogether. To this end, we introduce a new sampling-based online planning algorithm that can explicitly handle the risk of colliding with the environment and can switch between collision avoidance and collision exploitation. Central to the planner's capabilities is a novel joint optimization function that evaluates the effect of possible collisions using a reflect…
Hierarchical Task Model Predictive Control for Sequential Mobile Manipulation Tasks
Learning Systems and Robotics Lab（学习系统与机器人实验室）；Technical University of Munich（慕尼黑技术大学）；University of Toronto Institute for Aerospace Studies（多伦多大学航空航天研究所）；University of Toronto Robotics Institute（多伦多大学机器人研究所）；Munich Institute of Robotics and Machine Intelligence（慕尼黑机器人与机器智能研究所）；Vector Institute for Artificial Intelligence（人工智能向量研究所）
Interest in designing, manufacturing, and using autonomous robots has been rapidly growing during the most recent decade. The main motivation for this interest is the wide range of potential applications these autonomous systems can serve in. The applications include, but are not limited to, area coverage, patrolling missions, perimeter surveillance, search and rescue missions, and situational awareness. In this thesis, the area of control and state estimation in non-holonomic mobile robots is tackled. Herein, optimization based solutions for control and state estimation are designed, analyzed…
Fused deposition modeling (FDM) using mobile robots instead of the gantry-based 3D printer enables additive manufacturing at a larger scale with higher speed. This introduces challenges including accurate localization, control of the printhead, and design of a stable mobile manipulator with low vibrations and proper degrees of freedom. We proposed and developed a low-cost non-holonomic mobile 3D printing system guided by a projector via learning-based visual servo-ing. It requires almost no manual calibration of the system parameters. Using a regular top-down projector without any expensive ex…
In recent years, the use of non-analytical methods of computing such as fuzzy logic, evolutionary computation, and neural networks has demonstrated the utility and potential of these paradigms for intelligent control of mobile robot navigation. In this paper, a theoretical model of a fuzzy based controller for an autonomous mobile robot is developed. The paper begins with the mathematical model of the robot that involves the kinematic model. Then, the fuzzy logic controller is developed and discussed in detail. The proposed method is successfully tested in simulations, and it compares the effe…
An important capability of autonomous multi-robot systems is to prevent collision among the individual robots. One approach to this problem is to plan conflict-free trajectories and let each of the robots follow its pre-planned trajectory. A widely used practical method for multi-robot trajectory planning is prioritized planning, which has been shown to be effective in practice, but is in general incomplete. Formal analysis of instances that are provably solvable by prioritized planning is still missing. Moreover, prioritized planning is a centralized algorithm, which may be in many situations…
Physics Residual Dynamics and Reduced Order Whole-Body Planning for Obstacle Aware Human Robot Cloth CoTransportation
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)（穆罕默德·本·扎耶德人工智能大学）；Technical University of Munich (TUM)（慕尼黑工业大学）；Tampere University（坦佩雷大学）；Aalto University（阿尔托大学）
Technische Universität Ilmenau（伊尔梅瑙工业大学）；University of Stuttgart（斯图加特大学）
Data-driven surrogate models of dynamical systems based on the extended dynamic mode decomposition are nowadays well-established and widespread in applications. Further, for non-holonomic systems exhibiting a multiplicative coupling between states and controls, the usage of bi-linear surrogate models has proven beneficial. However, an in-depth analysis of the approximation quality and its dependence on different hyperparameters based on both simulation and experimental data is still missing. We investigate a differential-drive mobile robot to close this gap and provide first guidelines on the …
Bristol Robotics Laboratory, The University of Bristol（布里斯托尔机器人实验室，布里斯托尔大学）；Visual Information Laboratory, The University of Bristol（视觉信息实验室，布里斯托尔大学）；Department of Electrical and Electronic Engineering, The University of Manchester（曼彻斯特大学电气与电子工程系）；The Department of Computer Science and Engineering & The Department of Ophthalmology, The University of California, San Diego（加利福尼亚大学圣地亚哥分校计算机科学与工程系及眼科系）；Hangzhou ATG Intelligent Technology Co. Ltd.（杭州ATG智能科技有限公司）；Amazon（亚马逊公司）；The University of California, San Diego（加利福尼亚大学圣地亚哥分校）；The University of Manchester（曼彻斯特大学）；The University of Bristol（布里斯托尔大学）；Amazon, Seattle, USA（亚马逊公司（西雅图））；The Department of Ophthalmology, The University of California, San Diego（加利福尼亚大学圣地亚哥分校眼科系）
This paper presents an agile reactive navigation strategy for driving a non-holonomic ground vehicle around a preset course of gates in a cluttered environment using a low-cost processor array sensor. This enables machine vision tasks to be performed directly upon the sensor's image plane, rather than using a separate general-purpose computer. We demonstrate a small ground vehicle running through or avoiding multiple gates at high speed using minimal computational resources. To achieve this, target tracking algorithms are developed for the Pixel Processing Array and captured images are then pr…
This paper presents the design of a small aerial robot for inhabited microgravity environments, such as orbiting space stations (e.g., ISS). In particular, we target a fleet of robots, called Space CoBots, for collaborative tasks with humans, such as telepresence and cooperative mobile manipulation. The design is modular, comprising an hexrotor based propulsion system, and a stack of modules including batteries, cameras for navigation, a screen for telepresence, a robotic arm, space for extension modules, and a pair of docking ports. These ports can be used for docking and for mechanically att…
This paper presents a constrained-optimization formulation for the prioritized execution of learned robot tasks. The framework lends itself to the execution of tasks encoded by value functions, such as tasks learned using the reinforcement learning paradigm. The tasks are encoded as constraints of a convex optimization program by using control Lyapunov functions. Moreover, an additional constraint is enforced in order to specify relative priorities between the tasks. The proposed approach is showcased in simulation using a team of mobile robots executing coordinated multi-robot tasks.
Institute of Industrial and Control Engineering (IOC), Universitat Politècnica de Catalunya (UPC) – Barcelona Tech（加泰罗尼亚理工大学巴塞罗那科技学院工业与控制工程研究所）
Physics-based motion planning is a challenging task, since it requires the computation of the robot motions while allowing possible interactions with (some of) the obstacles in the environment. Kinodynamic motion planners equipped with a dynamic engine acting as state propagator are usually used for that purpose. The difficulties arise in the setting of the adequate forces for the interactions and because these interactions may change the pose of the manipulatable obstacles, thus either facilitating or preventing the finding of a solution path. The use of knowledge can alleviate the stated dif…
In this paper, a novel dual-mode robust model predictive control (MPC) approach is proposed for solving the tracking control problem of non-holonomoic mobile robots with additive bounded disturbance. To reduce the negative effect of disturbance and drive the state of real system closer to the one of nominal system , a robust reference signal is introduced into the cost function of MPC. In order to reduced the computation burden caused by online optimization of MPC and further improve the tracking accuracy, a dual-mode control strucuture consisting of the robust MPC and the local nonlinear robu…
In this paper, we develop estimation and control methods for quickly reacting to collisions between omnidirectional mobile platforms and their environment. To enable the full-body detection of external forces, we use torque sensors located in the robot's drivetrain. Using model based techniques we estimate, with good precision, the location, direction, and magnitude of collision forces, and we develop an admittance controller that achieves a low effective mass in reaction to them. For experimental testing, we use a facility containing a calibrated collision dummy and our holonomic mobile platf…
Koopman operator theory has served as the basis to extract dynamics for nonlinear system modeling and control across settings, including non-holonomic mobile robot control. There is a growing interest in research to derive robustness (and/or safety) guarantees for systems the dynamics of which are extracted via the Koopman operator. In this paper, we propose a way to quantify the prediction error because of noisy measurements when the Koopman operator is approximated via Extended Dynamic Mode Decomposition. We further develop an enhanced robot control strategy to endow robustness to a class of…
Technische Universität Dortmund（多特蒙德工业大学）；International Institute of Information Technology Bangalore（班加罗尔国际信息技术学院）
In this paper, the collision avoidance problem for non-holonomic robots moving at constant linear speeds in the 2-D plane is considered. The maneuvers to avoid collisions are designed using dynamic vortex potential fields (PFs) and their negative gradients; this formulation leads to a reciprocal behaviour between the robots, denoted as being cooperative. The repulsive field is selected as a function of the velocity and position of a robot relative to another and introducing vorticity in its definition guarantees the absence of local minima. Such a repulsive field is activated by a robot only w…
Mobile robots are increasingly populating homes, hospitals, shopping malls, factory floors, and other human environments. Human society has social norms that people mutually accept; obeying these norms is an essential signal that someone is participating socially with respect to the rest of the population. For robots to be socially compatible with humans, it is crucial for robots to obey these social norms. In prior work, we demonstrated a Socially-Aware Navigation (SAN) planner, based on Pareto Concavity Elimination Transformation (PaCcET), in a hallway scenario, optimizing two objectives so …
Federal Research Center for Computer Science and Control of RAS（俄罗斯科学院计算机科学与控制联邦研究中心）；Higher School of Economics（高等经济学院）；Peoples’ Friendship University of Russia (RUDN University)（俄罗斯人民友谊大学）；Kurchatov Institute（库尔恰托夫研究所）
Methods for centralized planning of the collision-free trajectories for a fleet of mobile robots typically solve the discretized version of the problem and rely on numerous simplifying assumptions, e.g. moves of uniform duration, cardinal only translations, equal speed and size of the robots etc., thus the resultant plans can not always be directly executed by the real robotic systems. To mitigate this issue we suggest a set of modifications to the prominent prioritized planner -- AA-SIPP(m) -- aimed at lifting the most restrictive assumptions (syncronized translation only moves, equal size an…
The primary objective of a safe navigation algorithm is to guide the object from its current position to the target position while avoiding any collision with the en-route obstacles, and the appropriate obstacle avoidance strategies are the key factors to ensure safe navigation tasks in dynamic environments. In this report, three different obstacle avoidance strategies for safe navigation in dynamic environments have been presented. The biologically-inspired navigation algorithm (BINA) is efficient in terms of avoidance time. The equidistant based navigation algorithm (ENA) is able to achieve …
Recently, a trend is emerging toward human-servicing autonomous mobile robots, with diverse applications including delivery of supplies in hospitals, hotels, or labs where personnel are scarce, or reacting to indoor emergencies. However, existing autonomous mobile robot (AMR) motion is slow and inefficient, a foundational barrier to proliferation of human-servicing applications. This research has developed a motion control architecture that demonstrates the potential of several algorithms for increasing speed and efficiency. These include a novel PI(t)D(t) controller that sets integral and der…
University of Birmingham（伯明翰大学）；Texas Tech University（得克萨斯理工大学）；SUNY at Binghamton（纽约州立大学宾汉姆顿分校）
This paper describes an architecture for robots that combines the complementary strengths of probabilistic graphical models and declarative programming to represent and reason with logic-based and probabilistic descriptions of uncertainty and domain knowledge. An action language is extended to support non-boolean fluents and non-deterministic causal laws. This action language is used to describe tightly-coupled transition diagrams at two levels of granularity, with a fine-resolution transition diagram defined as a refinement of a coarse-resolution transition diagram of the domain. The coarse-r…
University of Southern California（南加利福尼亚大学）；Robert Bosch GmbH（罗伯特·博世股份有限公司）
Planning smooth and energy-efficient motions for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics. Over the past decades, a wide variety of motion planners, steer functions and path-improvement techniques have been proposed for such non-holonomic systems. With the objective of comparing this large assortment of state-of-the-art motion-planning techniques, we introduce a novel open-source motion-planning benchmark for wheeled mobile robots, whose scenarios resemble real-world applications (such as navigating warehouse…
University of Edinburgh（爱丁堡大学）；University of Oxford（牛津大学）
Path planning and collision avoidance are challenging in complex and highly variable environments due to the limited horizon of events. In literature, there are multiple model- and learning-based approaches that require significant computational resources to be effectively deployed and they may have limited generality. We propose a planning algorithm based on a globally stable passive controller that can plan smooth trajectories using limited computational resources in challenging environmental conditions. The architecture combines the recently proposed fractal impedance controller with elasti…
Bikebot manipulation has advantages of the single-track robot mobility and manipulation dexterity. We present a coordinated pose control of mobile manipulation with the stationary bikebot. The challenges of the bikebot manipulation include the limited steering balance capability of the unstable bikebot and kinematic redundancy of the manipulator. We first present the steering balance model to analyze and explore the maximum steering capability to balance the stationary platform. A balancing equilibrium manifold is then proposed to describe the necessary condition to fulfill the simultaneous pl…
Express companies are deploying more robotic sorting systems, where mobile robots are used to sort incoming parcels by destination. In this study, we propose an integrated assignment and path-finding method for robots in such sorting systems. The method has two parts: offline and online. In the offline part, we represent the system as a traffic flow network, develop an approximate delay function using stochastic models, and solve the min-cost network flow problem. In the online part, robots are guided through the system according to the calculated optimal flow split probability. The online cal…
SRM Institute of Science and Technology（SRM科学技术学院）；University of Modena and Reggio Emilia（摩德纳-雷焦艾米利亚大学）
This paper presents a distributed multi-robot printing method which utilizes an optimization approach to decompose and allocate a printing task to a group of mobile robots. The motivation for this problem is to minimize the printing time of the robots by using an appropriate task decomposition algorithm. We present one such algorithm which decomposes an image into rasterized geodesic cells before allocating them to the robots for printing. In addition to this, we also present the design of a numerically controlled holonomic robot capable of spraying ink on smooth surfaces. Further, we use this…
Autonomous navigation of mobile robots is a well studied problem in robotics. However, the navigation task becomes challenging when multi-robot systems have to cooperatively navigate dynamic environments with deadlock-prone layouts. We present a Distributed Timed Elastic Band (DTEB) Planner that combines Prioritized Planning with the online TEB trajectory Planner, in order to extend the capabilities of the latter to multi-robot systems. The proposed planner is able to reactively avoid imminent collisions as well as predictively resolve potential deadlocks among a team of robots, while navigati…
When a mobile robot lacks high onboard computing or networking capabilities, it can rely on remote computing architecture for its control and autonomy. This paper introduces a novel collaborative Simulation Twin (ST) strategy for control and autonomy on resource-constrained robots. The practical implementation of such a strategy entails a mobile robot system divided into a cyber (simulated) and physical (real) space separated over a communication channel where the physical robot resides on the site of operation guided by a simulated autonomous agent from a remote location maintained over a net…
Towards Safe Maneuvering of Double-Ackermann-Steering Robots with a Soft Actor-Critic Framework
Univ. Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800（波尔多大学、国家科学研究中心、波尔多国立理工学院、LaBRI、UMR 5800）；School of Computer Science, University of Nottingham, UK（nottingham大学计算机科学学院）；Instituto de Investigación en Ingeniería de Aragón (I3A), Universidad de Zaragoza（阿拉贡工程研究所（I3A）、 Zaragoza大学）
