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Recently, a diverse range of robots with various functionalities have become a part of our daily lives. However, these robots either lack an arm or have less capable arms, mainly used for gestures. Another characteristic of the robots is that they are wheeled-type robots, restricting their operation to even surfaces. Several software platforms proposed in prior research have often focused on quadrupedal robots equipped with manipulators. However, many of these platforms lacked a comprehensive system combining perception, navigation, locomotion, and manipulation. This research introduces a software framework for clearing household objects with a quadrupedal robot. The proposed software framework utilizes the perception of the robot's environment through sensor inputs and organizes household objects to their designated locations. The proposed framework was verified by experiments within a simulation environment resembling the conditions of the RoboCup@Home 2021-virtual competition involving variations in objects and poses, where outcomes demonstrate promising performance. [ABSTRACT FROM AUTHOR]

This paper describes a method for obtaining a mobile manipulator's motion sequence by indicating a goal-hand pose. The proposed method entails recording various robot motions as a large number of motion sequences and associated swept volumes (SVs) and then selecting the most appropriate SV for the current situation. In addition, the motion sequences can be altered while the robot is in motion, and the transition motion is generated using sequential quadratic programming, enabling the robot to avoid collisions with obstacles found after it has begun to move. The proposed method's performance is verified by simulation to confirm the appropriate amount of data and the method's superiority. [ABSTRACT FROM AUTHOR]

In this paper, we present a direct drive brush-shaped tool developed for the use of robotic vine suckering. Direct drive design philosophy allows for precise and high bandwidth control of the torque exerted by the brush. Besides limiting the torque exerted onto the plant, this kind of design philosophy allows the brush to be used as a torque sensor. High bandwidth torque feedback from the tool is used to enable a position controlled robot arm to perform the suckering task without knowing the exact position and shape of the trunk of the vine. An experiment was conducted to investigate the dependency of the applied torque on the overlap between the brush and the obstacle. The results of the experiment indicate a quadratic relationship between torque and overlap. This quadratic function is estimated and used for compliant trunk shape following. A trunk shape following experiment demonstrates the utility of the presented tool to be used as a sensor for compliant robot arm control. The shape of the trunk is estimated by tracking the motion of the robot arm during the experiment. [ABSTRACT FROM AUTHOR]

In underwater environments, ensuring people's safety is complicated, with potentially life-threatening outcomes, especially when divers have to work in deeper conditions. To improve the available solutions for working with robots in this kind of environment, we propose the validation of a control strategy for robots when taking objects from the seabed. The control strategy proposed is based on acceleration feedback in the model of the system. Using this model, the reference values for position, velocity and acceleration are estimated, and then the position error signal can be computed. When the desired position is obtained, it is possible to then obtain the position error. The validation was carried out using three different objects: a ball, a bottle, and a plant. The experiment consisted of using this control strategy to take those objects, which the robot carried for a moment to validate the stabilisation control and reference following the control in terms of angle and depth. The robot was operated by a pilot from outside of the pool and was guided using a camera and sonar in a teleoperated way. As an advantage of this control strategy, the model upon which the robot is based is decoupled, allowing control of the robot for each uncoupled plane, this being the main finding of these tests. This demonstrates that the robot can be controlled by a control strategy based on a decoupled model, taking into account the hydrodynamic parameters of the robot. [ABSTRACT FROM AUTHOR]

This paper presents an approach that generates the overall trajectory of mobile manipulators for a complex mission consisting of several sub-tasks. Parametric dynamic movement primitives (PDMPs) can quickly generalize the online motion of robot manipulation by learning multiple demonstrations in offline. However, regarding complex missions consisting of multiple sub-tasks, a large number of demonstrations are required for full generalization, which is impractical. In this paper, we propose a framework that reduces the number of demonstrations for a complex mission. In the proposed method, complex demonstrations are segmented into multiple unit motions representing sub-tasks, and one PDMP is formed per each segment, resulting in multiple PDMPs. The phase decision process determines which sub-task and associated PDMPs to be executed online, allowing multiple PDMPs to be autonomously configured within an integrated framework. In order to generalize the execution time and regional goal in each phase, the Gaussian process regression (GPR) is applied. Simulation results from two different scenarios confirm that the proposed framework not only effectively reduces the number of demonstrations but also improves generalization performance. The actual experiments also demonstrate that the mobile manipulators effectively perform complex missions through the proposed framework. Note to Practitioners—This paper presents an approach of learning from demonstration (LfD) to generalize complex movements of robots. Parametric dynamic movement primitives (PDMPs) compute styles of movements from multiple demonstrations. However, the complexity of the PDMP increases as the mission involves more sub-tasks. In this paper, we resolve this issue by segmenting the complex mission into multiple sub-tasks and configuring multiple PDMPs. This work effectively reduces the number of required demonstrations for PDMPs, moderates the complexity of the algorithm. Also, the proposed approach allows flexible sub-task sequencing. It enables the mission in an unlearned sequence or a new combination of sub-tasks. The proposed approach is validated in both simulation and experimental results. Our approach is applicable for complex missions whose sub-tasks are clearly identified [ABSTRACT FROM AUTHOR]

Tidying up a household environment using a mobile manipulator poses various challenges in robotics, such as adaptation to large real-world environmental variations, and safe and robust deployment in the presence of humans. The Partner Robot Challenge in World Robot Challenge (WRC) 2020, a global competition held in September 2021, benchmarked tidying tasks in real home environments, and, importantly, tested for full system performances. For this challenge, we developed an entire household service robot system, which leverages a data-driven approach to adapt to numerous edge cases that occur during the execution, instead of classical manual pre-programmed solutions. In this paper, we describe the core ingredients of the proposed robot system, including visual recognition, object manipulation, and motion planning. Our robot system won the second prize, verifying the effectiveness and potential of data-driven robot systems for mobile manipulation in home environments. [ABSTRACT FROM AUTHOR]

This study presents the method of robotic rock-and-walk manipulation for dynamic, nonprehensile object locomotion. The object, which is in contact with an environmental surface, is basically manipulated to rock from side to side about the contact point periodically by the robot system. In the meantime, the passive dynamics due to gravity enables the object to roll along a zigzag path that leads to a forward walk. Rock-and-walk is a special-purpose method that enables the transport of a certain class of objects, which are too large, heavy to apply other primary methods such as grasping- or pushing-based operations. Our work is motivated by an interesting question in archaeology, how the giant statues of Easter Island (known as “moai”) were transported several hundred years ago, and a recent demonstration performed by archaeologists that it is possible to walk the statue by periodic rocking. We present a detailed study of the dynamics, kinematics, and mechanics of the object-robot-environment system, and devise a feedback control strategy for rock-and-walk gaiting through the effective regulation of the object’s energy and posture. An extensive set of experiments demonstrate the viability and practicality of our approach in diverse settings: Caging-based single-robot manipulation and cable-driven dual-robot manipulation using manipulator arms and aerial robots. [ABSTRACT FROM AUTHOR]

Mobile manipulators are being deployed for transporting parts between machines and work stations in warehouses and shop floors. To increase the efficiency of operations, these mobile manipulators are required to complete the tasks as fast as possible. Picking up parts with the manipulator while the mobile base is moving decreases the time required to complete the transportation task and increases the efficiency of operations. However, motions of the manipulator on a moving platform can be risky, and hence, it is desired that the manipulator starts and ends its motions as close as possible to the part being picked up. In this article, we present a bidirectional sampling-based scheme for generating such manipulator trajectories for a given mobile base trajectory for pickup and transportation. Our approach implicitly determines the location of the mobile base where the manipulator motion starts and ends as well as where grasping happens. It also determines which grasping pose to use for picking up the part. Furthermore, we have presented the techniques to reduce the manipulator motion time (span time) and the computation time. Our approach enables us to reduce span time on average by 35% with a $16\times $ reduction in the computation time compared to the RRT-based baseline methods. Note to Practitioners—Transportation of objects is a crucial application in industrial and warehouse environments. Conveyor belts and AGVs are typically used for such applications as they provide an efficient mode of transportation of a large number of objects. However, they may not provide the flexibility which mobile manipulators bring in for small-scale operations. The method presented in this article provides a way to increase the efficiency of operation for mobile manipulators for transportation tasks. We attempt to reduce the risks of the manipulator colliding with expensive equipment and moving obstacles by making sure that the manipulator moves only when needed for picking up objects. Moreover, the method can be used to pick up and transport a variety of parts in different ways using a two-fingered gripper. The method can also easily incorporate different types of grippers and mobile platforms. [ABSTRACT FROM AUTHOR]

Tidy-up tasks by service robots in home environments are challenging in robotics applications because they involve various interactions with the environment. In particular, robots are required not only to grasp, move, and release various home objects but also to plan the order and positions for placing the objects. In this paper, we propose a novel planning method that can efficiently estimate the order and positions of the objects to be tidied up by learning the parameters of a probabilistic generative model. The model allows a robot to learn the distributions of the co-occurrence probability of the objects and places to tidy up using the multimodal sensor information collected in a tidied environment. Additionally, we develop an autonomous robotic system to perform the tidy-up operation. We evaluate the effectiveness of the proposed method by an experimental simulation that reproduces the conditions of the Tidy Up Here task of the World Robot Summit 2018 international robotics competition. The simulation results show that the proposed method enables the robot to successively tidy up several objects and achieves the best task score among the considered baseline tidy-up methods. [ABSTRACT FROM AUTHOR]

Various studies on autonomous robots that perform physical tasks in living environments are being conducted at present to solve the social problems of an aging society with a low birth rate. However, because it remains difficult for all robots to work autonomously in complicated environments, remote control robots may be useful for practical applications. As the purpose of remote control robots is to make direct connections between the operator and user, they may reduce affinity between the robot and the user. In this study, we define autonomous remote control robots with the aspects of both autonomy and remote operation explicitly. Affinity is compared among autonomous remote control robots, remote control robots, and autonomous robots, through controlled experiments on interactions in fetch-and-carry tasks using a domestic mobile manipulator, Human Support Robot, on a test field that is compliant with the World Robot Summit 2020 Rulebook. The results demonstrate that affinity exhibits the following order: autonomous robots, autonomous remote control robots, and remote control robots. Considering that autonomous robots remain under development, autonomous remote control robots may be beneficial for expanding the abilities of physical tasks and social acceptance. [ABSTRACT FROM AUTHOR]

As the retail industry keeps expanding and shortage of workers increasing, there is a need for autonomous manipulation of products to support retail operations. The increasing amount of products and customers in establishments such as convenience stores requires the automation of restocking, disposing and straightening of products. The manipulation of products needs to be time-efficient, avoid damaging products and beautify the display of products. In this paper, we propose a robotic system to restock shelves, dispose expired products, and straighten products in retail environments. The proposed mobile manipulator features a custom-made end effector with compact and compliant design to safely and effectively manipulate products in retail stores. Through experiments in a convenience store scenario, we verify the effectiveness of our system to restock, dispose and rearrange items. [ABSTRACT FROM AUTHOR]

In human-robot collaboration, robots interact directly and safely with humans in a shared workspace without protective guards. This paper presents the design of OmniMan, which is a mobile manipulator for human-robot collaboration consisting of an omnidirectional mobile platform and a lightweight robotic arm. Mobile manipulators extend the workspace of manipulators (robotic arms) by mounting them on mobile platforms. The mobile platform is driven by Mecanum wheels, which provide 3 degrees of freedom in motion. The paper develops the kinematic model of the whole system including platform and manipulator. Furthermore the overall controller structure for OmniMan including the realtime synchronization of platform and manipulator is described. [ABSTRACT FROM AUTHOR]

A task-space method is presented for the control of a head-raising articulated mobile robot, allowing the trajectory tracking of a tip of a gripper located on the head of the robot in various operations, e.g., picking up an object and rotating a valve. If the robot cannot continue moving because it reaches a joint angle limit, the robot moves away from the joint limit and changes posture by switching the allocation of lifted/grounded wheels. An articulated mobile robot with a gripper that can grasp objects using jamming transition was developed, and experiments were conducted to demonstrate the effectiveness of the proposed controller in operations. [ABSTRACT FROM AUTHOR]

In this work the topic of kinematic redundancy modelling and resolution for robotic mobile manipulators is considered. A set of redundancy parameters is introduced to define a general inverse kinematic procedure for mobile manipulators. Then, redundancy is treated as a non-linear optimization problem with the purpose of finding robot configurations that maximize the designed metric measures. Some strategies to design the optimization objective function are introduced in order to achieve desirable redundant behaviours, such as obstacles avoidance, mobile base motions reductions and dexterity optimization. Moreover, the robot controller has been developed following an object-oriented software architecture principle that allows to keep it general and robot independent. As a prove of reliability and generality of our approach, the same controller has been used to control several different mobile manipulators in a simulation environment, as well as a real KUKA youBot robot. [ABSTRACT FROM AUTHOR]

In this paper, a fuzzy system is trained to approximate the manipulability index and the inverted condition number of a mobile manipulator. The kinematic model of a mobile platform with the attached manipulator is fused using twist theory and certain dexterity measures are examined throughout the configuration space. A Takagi–Sugeno–Kang fuzzy system is designed to approximate the dexterity measures and it is evaluated both for its error and its efficiency in computational cost. The proposed methodology is proved as a very efficient approximation that can be utilized in real-time motion planning algorithms without significantly adding computational cost to the controller. [ABSTRACT FROM AUTHOR]

The paper proposes a method to improve flexibility of the motion planning process for mobile manipulators. The approach is based on the exploitation of perception data available only from simple proximity sensors distributed on the robot. Such data are used to correct pre-planned motions to cope with uncertainties and dynamic changes of the scene at execution time. The algorithm computes robot motion commands aimed at fulfilling the mission by combining two tasks at the same time, i.e. following the planned end-effector path and avoiding obstacles in the environment, by exploiting robot redundancy as well as handling priorities among tasks. Moreover, a technique to smoothly switch between the tasks is presented. To show the effectiveness of the method, four experimental case studies have been presented consisting in a place task executed by a mobile manipulator in an increasingly cluttered scene. [ABSTRACT FROM AUTHOR]

In order to develop an autonomous mobile manipulation system that works in an unstructured environment, a modified image-based visual servo (IBVS) controller using hybrid camera configuration is proposed in this paper. In particular, an eye-in-hand web camera is employed to visually track the target object while a stereo camera is used to measure the depth information online. A modified image-based controller is developed to utilize the information from the two cameras. In addition, a rule base is integrated into the visual servo controller to adaptively tune its gain based on the image deviation data so as to improve the response speed of the controller. A physical mobile manipulation system is developed and the developed IBVS controller is implemented. The experimental results obtained using the systems validate the developed approach. [ABSTRACT FROM AUTHOR]

Abstract: In this article, we describe efficient methods for tackling everyday mobile manipulation tasks that require object pick-up. In order to achieve real-time performance in complex environments, we focus our approach on fast yet robust solutions. For 3D perception of objects on planar surfaces, we develop scene segmentation methods that process depth images in real-time at high frame rates. We efficiently plan feasible, collision-free grasps for the segmented objects directly from the perceived point clouds to achieve fast execution times. We evaluate our approaches quantitatively in lab experiments and also report on the successful integration of our methods in public demonstrations at RoboCup@Home competitions in 2011 and 2012. [Copyright &y& Elsevier]

We describe an integrated strategy for planning, perception, state estimation and action in complex mobile manipulation domains based on planning in the belief space of probability distributions over states using hierarchical goal regression (pre-image back-chaining). We develop a vocabulary of logical expressions that describe sets of belief states, which are goals and subgoals in the planning process. We show that a relatively small set of symbolic operators can give rise to task-oriented perception in support of the manipulation goals. An implementation of this method is demonstrated in simulation and on a real PR2 robot, showing robust, flexible solution of mobile manipulation problems with multiple objects and substantial uncertainty. [ABSTRACT FROM AUTHOR]

The open hardware mobile manipulator (OHMM) is a new open platform with a unique combination of features for teaching robotics software and algorithms. On-board low- and high-level processors support real-time embedded programming and motor control, as well as higher-level coding with contemporary libraries. Full hardware designs and software source codes are available under free licenses enabling the community to adapt and update the design as the field (and available hardware) evolves. Digital manufacturing (3-D printing and laser cutting) methods, now available as low-cost Internet services, enable OHMM to be easily modified and to be built from scratch for a competitive price. Five hands-on curriculum modules are presented that use OHMM to teach robotics software and algorithms at the undergraduate and graduate levels, and results are presented based on student performance and feedback. [ABSTRACT FROM AUTHOR]

We present a rollover prevention control law for wheeled mobile manipulators based on the invariance control framework, and that makes use of recursively calculated analytic gradients of the mobile manipulator’s zero moment point. Our controller relaxes many of the assumptions made in existing approaches, and enhances robustness through the use of exact gradient information. Numerical experiments demonstrate the improved performance of our controller vis-à-vis existing rollover prevention schemes. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the development of a prototype vision-guided forklift system for the automatic engagement of pallets. The system is controlled using the visual guidance method of mobile camera-space manipulation, which is capable of achieving a high level of precision in positioning and orienting mobile manipulator robots without relying on camera calibration. The paper contains development of the method, the development of a prototype forklift as well as experimental results in actual pallet engagement tasks. The technology could be added to AGV systems enabling them to engage arbitrarily located pallets. It also could be added to standard forklifts as an operator assist capability. [Copyright &y& Elsevier]

This paper presents a new teleoperation approach using a virtual spring, and local contact force control on the slave robot. The operational space framework provides the control structure needed to achieve decoupled task dynamics. A virtual spring connects the master and slave systems and a closed-loop force controller compensates for the dynamics of the slave system, rendering transparent the effector of the slave robotic system. The active force control approach allows the desired motion and contact forces to be combined in a single force command. The required performance and robustness of force control are achieved by a full state reconstruction using a modified Kalman estimator, which addresses disturbances and modeling uncertainties. The performance of both telepresence and force control are further improved by on-line stiffness estimation of the object in contact with the effector. The redundancy of the mobile manipulation system is addressed through a decoupled decomposition of task amid posture dynamics. [ABSTRACT FROM AUTHOR]

This paper introduces a reactive self-collision avoidance algorithm for differentially driven mobile manipulators. The proposed method mainly focuses on self-collision between a manipulator and the mobile robot. We introduce the concept of a distance buffer border (DBB), which is a 3D curved surface enclosing a buffer region of the mobile robot. The region has the thickness equal to buffer distance. When the distance between the manipulator and mobile robot is less than the buffer distance, which means the manipulator lies inside the buffer region of the mobile robot, the proposed strategy is to move the mobile robot away from the manipulator in order for the manipulator to be placed outside the border of the region, the DBB. The strategy is achieved by exerting force on the mobile robot. Therefore, the manipulator can avoid self-collision with the mobile robot without modifying the predefined motion of the manipulator in a world Cartesian coordinate frame. In particular, the direction of the force is determined by considering the non-holonomic constraint of the differentially driven mobile robot. Additionally, the reachability of the manipulator is considered to arrive at a configuration in which the manipulator can be more maneuverable. In this respect, the proposed algorithm has a distinct advantage over existing avoidance methods that do not consider the non-holonomic constraint of the mobile robot and push links away from each other without considering the workspace. To realize the desired force and resulting torque, an avoidance task is constructed by converting them into the accelerations of the mobile robot. The avoidance task is smoothly inserted with a top priority into the controller based on hierarchical quadratic programming. The proposed algorithm was implemented on a differentially driven mobile robot with a 7-DOFs robotic arm and its performance was demonstrated in various experimental scenarios. [ABSTRACT FROM AUTHOR]

Mobile manipulation, which has more flexibility than fixed-base manipulation, has always been an important topic in the field of robotics. However, for sophisticated operation in complex environments, efficient localization and dynamic tracking grasp still face enormous challenges. To address these challenges, this paper proposes a mobile manipulation method integrating laser-reflector-enhanced adaptive Monte Carlo localization (AMCL) algorithm and a dynamic tracking and grasping algorithm. First, by fusing the information of laser-reflector landmarks to adjust the weight of particles in AMCL, the localization accuracy of mobile platforms can be improved. Second, deep-learning-based multiple-object detection and visual servo are exploited to efficiently track and grasp dynamic objects. Then, a mobile manipulation system integrating the above two algorithms into a robotic with a 6-degrees-of-freedom (DOF) operation arm is implemented in an indoor environment. Technical components, including localization, multiple-object detection, dynamic tracking grasp, and the integrated system, are all verified in real-world scenarios. Experimental results demonstrate the efficacy and superiority of our method. [ABSTRACT FROM AUTHOR]

Mobile manipulation has a broad range of applications in robotics. However, it is usually more challenging than fixed-base manipulation due to the complex coordination of a mobile base and a manipulator. Although recent works have demonstrated that deep reinforcement learning is a powerful technique for fixed-base manipulation tasks, most of them are not applicable to mobile manipulation. This paper investigates how to leverage deep reinforcement learning to tackle whole-body mobile manipulation tasks in unstructured environments using only on-board sensors. A novel mobile manipulation system which integrates the state-of-the-art deep reinforcement learning algorithms with visual perception is proposed. It has an efficient framework decoupling visual perception from the deep reinforcement learning control, which enables its generalization from simulation training to real-world testing. Extensive simulation and experiment results show that the proposed mobile manipulation system is able to grasp different types of objects autonomously in various simulation and real-world scenarios, verifying the effectiveness of the proposed mobile manipulation system. [ABSTRACT FROM AUTHOR]

As demands on pragmatic solutions of robotics technology increase in the manufacturing industry, deep affinities between research experts and industry users are required. The European Robotics Challenges (EuRoC) research project has proposed a scientific competition and matched up research labs with industrial end users to establish challenger teams to develop and test solutions that will be applied in the real context of the industrial end-users. The paper reports the result of TIMAIRIS who is one of 6 challenger teams to advance to the final stage out of 103 teams and technical details used in the Challenge 2 - Shop Floor Logistics and Manipulation. To address the requirements and achieve the objectives of the challenge, a skill-based anytime agent architecture has been developed and extended to make the team focus on the challenging research that addresses real issues in the user environments. Finally, shop floor logistics and manipulation scenarios have been developed and demonstrated in a realistic environment for autonomous packaging. • The proposed Skill-based Anytime Agent Architecture (SAAA) enables a robot to start at any state. • The SAAA enhances online and offline efficiency. • As the result of the Stage II evaluations, TIMAIRIS has been selected to advance to the final stage of the EuRoC project. • During the showcase evaluation, it has been demonstrated that autonomous blank feeding is possible in a realistic industrial environment. [ABSTRACT FROM AUTHOR]