DOF Robotic Arm Research Articles

Learning to Search in Task and Motion Planning With Streams

Task and motion planning problems in robotics combine symbolic planning over discrete task variables with motion optimization over continuous state and action variables. Recent works such as PDDLStream [1]garrett2020pddlstream have focused on optimistic planning with an incrementally growing set of objects until a feasible trajectory is found. However, this set is exhaustively expanded in a breadth-first manner, regardless of the logical and geometric structure of the problem at hand, which makes long-horizon reasoning with large numbers of objects prohibitively time-consuming. To address this issue, we propose a geometrically informed symbolic planner that expands the set of objects and facts in a best-first manner, prioritized by a Graph Neural Network that is learned from prior search computations. We evaluate our approach on a diverse set of problems and demonstrate an improved ability to plan in difficult scenarios. We also apply our algorithm on a 7DOF robotic arm in block-stacking manipulation tasks.

KDF: Kinodynamic Motion Planning via Geometric Sampling-Based Algorithms and Funnel Control

We integrate sampling-based planning techniques with funnel-based feedback control to develop KDF, a new framework for solving the kinodynamic motion-planning problem via funnel control. The considered systems evolve subject to complex, nonlinear, and uncertain dynamics (also known as differential constraints). First, we use a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">geometric</i> planner to obtain a high-level safe path in a user-defined extended free space. Second, we develop a low-level funnel control algorithm that guarantees safe tracking of the path by the system. Neither the planner nor the control algorithm uses information on the underlying dynamics of the system, which makes the proposed scheme easily distributable to a large variety of different systems and scenarios. Intuitively, the funnel control module is able to implicitly accommodate the dynamics of the system, allowing hence the deployment of purely geometrical motion planners. Extensive computer simulations and hardware experiments with a 6-DOF robotic arm validate the proposed approach.

Positioning Control of Robotic Manipulators Subject to Excitation from Non-Ideal Sources

The present work proposes the use of a hybrid controller combining concepts of a PID controller with LQR and a feedforward gain to control the positioning of a 2 DOF robotic arm with flexible joints subject to non-ideal excitations. To characterize the performance of the controls, two cases were studied. The first case considered the positioning control of the two links in fixed positions, while the second case considered the situation in which the second link is in rotational movement and the first one stays in a fixed position, representing a system with a non-ideal excitation source. In addition to the second case, the sensitivity of the proposed controls for changes in the length and mass of the second link in the rotational movement was analyzed. The results of the simulations showed the effectiveness of the controls, demonstrating that the PID control combined with feedforward gain provides the lowest error for both cases studied; however, it is sensitive to variations in the mass of the second link, in the case of rotational movements. The numerical results also revealed the effectiveness of the PD control obtained by LQR, presenting results similar to the PID control combined with feedforward gain, demonstrating the importance of the optimal control design.

Development of a prototype 6 degree of freedom robot arm

The study presents a design alternative, simulates the operation, and analyzes the new structure of the 6 DOF robot arm. The proposed robot model is based on reference shapes from AR3 robot arm, with modifications to details and structures to accommodate the actual and economic circumstances in Vietnam. Solidwork software was first utilized for the arm structure's design, strength testing, and optimization. The material is chosen with the goal of reducing production cost and ensuring the robot's operation properly. The study concludes by applying the topology optimization algorithm to a machine component to determine the optimal structure of the robot arm. To validating the design results, the prototype is manufacturers using CNC machine. The experimental results show the robot arm basic functions effectively. This research could be used as references for designing and manufacturing a 6 DOF robot arm with relative robot's structure.

2D/3D Wound Segmentation and Measurement Based on a Robot-Driven Reconstruction System

Chronic wounds, are a worldwide health problem affecting populations and economies as a whole. With the increase in age-related diseases, obesity, and diabetes, the costs of chronic wound healing will further increase. Wound assessment should be fast and accurate in order to reduce possible complications and thus shorten the wound healing process. This paper describes an automatic wound segmentation based on a wound recording system built upon a 7-DoF robot arm with an attached RGB-D camera and high-precision 3D scanner. The developed system represents a novel combination of 2D and 3D segmentation, where the 2D segmentation is based on the MobileNetV2 classifier and the 3D component is based on the active contour model, which works on the 3D mesh to further refine the wound contour. The end output is the 3D model of only the wound surface without the surrounding healthy skin and geometric parameters in the form of perimeter, area, and volume.

Vibro-Acoustic Sensing of Instrument Interactions as a Potential Source of Texture-Related Information in Robotic Palpation.

The direct tactile assessment of surface textures during palpation is an essential component of open surgery that is impeded in minimally invasive and robot-assisted surgery. When indirectly palpating with a surgical instrument, the structural vibrations from this interaction contain tactile information that can be extracted and analysed. This study investigates the influence of the parameters contact angle α and velocity v→ on the vibro-acoustic signals from this indirect palpation. A 7-DOF robotic arm, a standard surgical instrument, and a vibration measurement system were used to palpate three different materials with varying α and v→. The signals were processed based on continuous wavelet transformation. They showed material-specific signatures in the time-frequency domain that retained their general characteristic for varying α and v→. Energy-related and statistical features were extracted, and supervised classification was performed, where the testing data comprised only signals acquired with different palpation parameters than for training data. The classifiers support vector machine and k-nearest neighbours provided 99.67% and 96.00% accuracy for the differentiation of the materials. The results indicate the robustness of the features against variations in the palpation parameters. This is a prerequisite for an application in minimally invasive surgery but needs to be confirmed in realistic experiments with biological tissues.

Upgrading Gryphon PUMA Robot Arm Using ROS-MoveIt

Industrial and old lab robotic equipment can be upgraded and reused invery sophisticated applications such as robot arms if provided with an efficientmodular program or framework such as ROS (Robotics Operating system). In thispaper, we replace the old control system of the 5-DOF robot arm (completeGryphon Package 35-002-c) with the help of ROS MoveIt Motion PlanningFramework package to control motion planning and generate joints angles, URDF(Unified Robot Description format) used to create the robot model for ROS. Themicrocontroller is used to move the five stepping motors to move the end effectorin the desired pose: position and orientation using ROS and MoveIt capability.Thus, the robot should be upgradeable, and anyone who has ROS basic skills canimprove the arm functionality to use it in any desired application.

Learning-based collision-free planning on arbitrary optimization criteria in the latent space through cGANs

We propose a new method for collision-free planning using Conditional Generative Adversarial Networks (cGANs) to transform between the robot's joint space and a latent space that captures only collision-free areas of the joint space, conditioned by an obstacle map. Generating multiple plausible trajectories is convenient in applications such as the manipulation of a robot arm by enabling the selection of trajectories that avoids collision with the robot or surrounding environment. In the proposed method, various trajectories that avoid obstacles can be generated by connecting the start and goal state with arbitrary line segments in this generated latent space. Our method provides this collision-free latent space, after which any planner, using any optimization conditions, can be used to generate the most suitable paths on the fly. We successfully verified this method with a simulated and actual UR5e 6-DoF robotic arm. We confirmed that different trajectories could be generated depending on optimization conditions.

Design and Performance Verification of a Novel RCM Mechanism for a Minimally Invasive Surgical Robot.

Minimally invasive surgical robots have the advantages of high positioning accuracy, good stability, and flexible operation, which can effectively improve the quality of surgery and reduce the difficulty for doctors to operate. However, in order to realize the translation of the existing RCM mechanism, it is often necessary to add a mobile unit, which is often bulky and occupies most space above the patient's body, thus causing interference to the operation. In this paper, a new type of planar RCM mechanism is proposed. Based on this mechanism, a 3-DOF robotic arm is designed, which can complete the required motion for surgery without adding a mobile unit. In this paper, the geometric model of the mechanism is first introduced, and the RCM point of the mechanism is proven during the motion process. Then, based on the establishment of the geometric model of the mechanism, a kinematics analysis of the mechanism is carried out. The singularity, the Jacobian matrix, and the kinematic performance of the mechanism are analyzed, and the working space of the mechanism is verified according to the kinematic equations. Finally, a prototype of the RCM mechanism was built, and its functionality was tested using a master-slave control strategy.

Design and Development of a Low-Cost Vision-Based 6 DoF Assistive Feeding Robot for the Aged and Specially-Abled People

Human-Robot interaction plays a vital role in the service robotics field, especially to support old age-dependent people for socio-economic reasons. In this paper, an indigenous 3D printed 6 DoF robotic arm is proposed to support specially-abled people in their independent-feeding process. The objective of the present paper is to find the combination of optimal positional controllers such as CPID, FC, FPID and FOPID, which can handle the cubic reference input signal and can produce an output signal with minimal overshoot and lesser positional error. The reduced positional error helps the robotic arm to accurately reach the destination with minimal oscillations. This would reduce the wastage of food in the middle of the trajectory as well as at the destination. The technical challenge of the paper is to synchronize machine vision, robot kinematics and trajectory planning with robot control for multiple intermediate points, subjected to the cubic input signal. The feeding robotic arm is equipped with Intel© visual depth camera, which is in synchronization with the microcontroller, servo controller, and servo actuators. Here, six intermediate points were identified in the C-space using FK, among which, fuzzy controller was selected for the first two IPs, the GA optimized FOPID was selected for IP3 to IP5 and FPID was deployed for the last IP. The GA: FOPID produced a negligible overshoot of 0.67%, whereas FC and FPID produced an overshoot of 1.4% and 0.8% respectively. The positional error gap between GA: FOPID, FC and FPID was 0.9, and 0.6 Deg/sec respectively. The selection of combination of optimal controllers helps the manipulator to successfully deliver the food without wasting it. The repeatability of the feeding process is ensured by successfully conducting user testing on 20 users for 25 cycles.

Elasto-geometrical calibration of a hybrid mobile robot considering gravity deformation and stiffness parameter errors

• An elasto-geometrical calibration method taking into account structural and stiffness parameter errors is proposed for a hybrid mobile robot. • A compensation strategy comprehensively considering the pose errors of the 3-RCU parallel module and 2-DoF robotic arm is put forward to improve the accuracy of the robot. • Calibration experiments based on three different models are conducted and the accuracy of the robot before and after calibration is tested to show the validity of the proposed method. Hybrid mobile robots, which combine the advantages of serial and parallel robots and have the ability to realize processing in situ , have considerable application potential in the field of processing and manufacturing. In this paper, a hybrid mobile robot used for wind turbine blade polishing is presented. The robot combines an automated guided vehicle, a 2-DoF robotic arm, and a 3-RCU parallel module. To improve the accuracy, investigating the elasto-geometrical calibration of the robot is necessary. Considering that the 3-RCU parallel module has weak stiffness along the gravitational direction, the stiffness model was established to estimate the deformation caused by the gravity of the mobile platform, ball screws, and motors. Subsequently, a rigid-flexible coupling error model considering structural and stiffness parameter errors is established. Based on these, a parameter identification method for the simultaneous identification of structural and stiffness parameter errors is proposed herein. For the 2-DoF robotic arm with parallelogram mechanisms, an intuitive error model considering the posture error caused by the parallelogram mechanism errors is established. The regularized nonlinear least squares method was adopted for parameter identification. Thereafter, a compensation strategy for the hybrid mobile robot that comprehensively considers the pose errors of the 3-RCU parallel module and 2-DoF robotic arm is proposed. Finally, a verification experiment was performed on the prototype, and the results indicated that after elasto-geometrical calibration, the maximum/mean of the position and posture errors of the hybrid mobile robot decreased from 3.738 mm/2.573 mm to 0.109 mm/0.063 mm and 0.236°/0.179° to 0.030°/0.013°, respectively. Owing to the decrease in the robot pose errors, the quality of the polished surface was more uniform. The range and standard deviation of roughness distribution of the polished surface were reduced from 0.595 μm and 0.248 μm to 0.397 μm and 0.127 μm. The methods proposed herein have reference significance for elasto-geometrical calibration of other parallel or hybrid robots.

Modular Magnetorheological Actuator With High Torque Density and Transparency for the Collaborative Robot Industry

In the last decade, the development of simple and easy-to-use robotics has provided a significant step towards the democratization of collaborative robots, which can now work closely alongside humans. However, state-of-the-art cobots still provide safety at the cost of work-speed, which is purposely limited to avoid high-energy collisions. In order to increase safety and work speed simultaneously, force/impedance-controlled actuators with high dynamic performance, backdrivability and low-reflected inertia are of interest. In this letter, a novel robotic actuator architecture with two independent magnetorheological (MR) power chains is proposed, built and experimentally characterized. The modular 30 Nm robotic joint is shown to have similar size (85 X 85 X 124 mm), weight (1.1 kg) and torque density (27 Nm/kg) as the Universal Robot (UR) size 1 robotic joint, which relies on a Harmonic Drive (HD) gearbox, but with 150 times less inertia, high backdrivability (0.7% of max torque), high torque bandwidth (>70 Hz) and inherent torque-limiting that makes it immune to impacts. The dual MR power chain allows ultra-fast transparent interactions with bluezero backlash over half its torque range and peak torque when motor reversal is allowed. To illustrate the force/impedance control performance, a 3-DOF robotic arm is built and used to simulate virtual objects in both open and closed loop.

Kinematics modeling of six degrees of freedom humanoid robot arm using improved damped least squares for visual grasping

&lt;span lang="EN-US"&gt;The robotic arm has functioned as an arm in the humanoid robot and is generally used to perform grasping tasks. Accordingly, kinematics modeling both forward and inverse kinematics is required to calculate the end-effector position in the cartesian space before performing grasping activities. This research presents the kinematics modeling of six degrees of freedom (6-DOF) robotic arm of the T-FLoW humanoid robot for the grasping mechanism of visual grasping systems on the robot operating system (ROS) platform and CoppeliaSim. Kinematic singularity is a common problem in the inverse kinematics model of robots, but. However, other problems are mechanical limitations and computational time. The work uses the homogeneous transformation matrix (HTM) based on the Euler system of the robot for the forward kinematics and demonstrates the capability of an improved damped least squares (I-DLS) method for the inverse kinematics. The I-DLS method was obtained by improving the original DLS method with the joint limits and clamping techniques. The I-DLS performs better than the original DLS during the experiments yet increases the calculation iteration by 10.95%, with a maximum error position between the end-effector and target positions in path planning of 0.1 cm.&lt;/span&gt;

A Surgical Robotic System for Osteoporotic Hip Augmentation: System Development and Experimental Evaluation.

Minimally-invasive Osteoporotic Hip Augmentation (OHA) by injecting bone cement is a potential treatment option to reduce the risk of hip fracture. This treatment can significantly benefit from computer-assisted planning and execution system to optimize the pattern of cement injection. We present a novel robotic system for the execution of OHA that consists of a 6-DOF robotic arm and integrated drilling and injection component. The minimally-invasive procedure is performed by registering the robot and preoperative images to the surgical scene using multiview image-based 2D/3D registration with no external fiducial attached to the body. The performance of the system is evaluated through experimental sawbone studies as well as cadaveric experiments with intact soft tissues. In the cadaver experiments, distance errors of 3.28mm and 2.64mm for entry and target points and orientation error of 2.30° are calculated. Moreover, the mean surface distance error of 2.13mm with translational error of 4.47mm is reported between injected and planned cement profiles. The experimental results demonstrate the first application of the proposed Robot-Assisted combined Drilling and Injection System (RADIS), incorporating biomechanical planning and intraoperative fiducial-less 2D/3D registration on human cadavers with intact soft tissues.

Eye-in-Hand Robotic Arm Gripping System Based on Machine Learning and State Delay Optimization.

This research focused on using RGB-D images and modifying an existing machine learning network architecture to generate predictions of the location of successfully grasped objects and to optimize the control system for state delays. A five-finger gripper designed to mimic the human palm was tested to demonstrate that it can perform more delicate missions than many two- or three-finger grippers. Experiments were conducted using the 6-DOF robot arm with the five-finger and two-finger grippers to perform at least 100 actual machine grasps, and compared to the results of other studies. Additionally, we investigated state time delays and proposed a control method for a robot manipulator. Many studies on time-delay systems have been conducted, but most focus on input and output delays. One reason for this emphasis is that input and output delays are the most commonly occurring delays in physical or electronic systems. An additional reason is that state delays increase the complexity of the overall control system. Finally, it was demonstrated that our network can perform as well as a deep network architecture with little training data and omitting steps, such as posture evaluation, and when combined with the hardware advantages of the five-finger gripper, it can produce an automated system with a gripping success rate of over 90%. This paper is an extended study of the conference paper.

Iterative Learning Control for Vibration Suppression of a Robotic Arm

This paper presents a vibration control method for the vibration suppression of a robotic arm. To understand the causes of the vibration in the six-axis manipulator and then eliminate the vibration through an effective control method, the vibration control structure can be divided into two parts. First, variational mode decomposition (VMD) and the Hilbert–Huang transform (HHT) algorithm are integrated to analyze the vibration signal and extract the vibration characteristics. Second, a smooth trajectory planning method is used to eliminate the residual vibration. Then, a feedback controller and iterative learning controller are used for controlling the vibration to stabilize the system while compensating for the torque of the elastic-joint model and repetitive errors caused by the vibration through the repeated operation of the arm. In addition, to improve the iterative learning control (ILC) performance, the integration of VMD and the HHT is used to distinguish useless information. The ILC is able to learn more quickly and compensate for the error caused by the vibration. The proposed VMD-HHT iterative learning control for the elastic joint (VH-ILC-EJ) method, along with a laboratory-developed six-axis degree-of-freedom (6-DOF) robotic arm, has been numerically and experimentally validated for vibration suppression.

D.O.T. PAQUITOP, an Autonomous Mobile Manipulator for Hospital Assistance

The use of robotic technologies for caregiving and assistance has become a very interesting research topic in the field of robotics. Towards this goal, the researchers at Politecnico di Torino are developing robotic solutions for indoor assistance. This paper presents the D.O.T. PAQUITOP project, which aims at developing a mobile robotic assistant for the hospital environment. The mobile robot is composed of a custom omnidirectional platform, named PAQUITOP, a commercial 6 dof robotic arm, sensors for monitoring vital signs in patients, and a tablet to interact with the patient. To prove the effectiveness of this solution, preliminary tests were conducted with success in the laboratories of Politecnico di Torino and, thanks to the collaboration with the Onlus Fondazione D.O.T. and the medical staff of Molinette Hospital in Turin (Italy), at the hematology ward of Molinette Hospital.

Micro-Defect Inspection on Curved Surface Using a 6-DOF Robot Arm with One-Shot BRDF Imaging

The need for automated visual inspection in Japan is increasing due to labor shortages caused by the declining birthrate and aging population. We have developed an imaging system called One-shot BRDF (Bidirectional Reflectance Distribution Function), which can easily detect even micro-defects that are conventionally difficult to capture using parallel-beam illumination and an image sensor. By color-coding the direction of light, micro-defects can be instantly captured as a clear image. This paper proposes a novel micro-defect inspection system capable of automatically inspecting the surface of materials with complex shapes by mounting One-shot BRDF optics on the tip of a 6-degree-of-freedom (DOF) robot arm and scanning the material's surface. The 6-DOF robot arm can track the scanning trajectory and keep the optics squarely against the curved surface at a constant distance. We developed a simple algorithm to automatically determine the trajectory from the material's 3D CAD data so that the entire surface to be scanned can be inspected quickly and within the 6-DOF robot arm's range of movement. For high-speed and high-precision inspection, we built a nonlinear dynamic model of the 6-DOF robot arm and model-based control to track the trajectory while suppressing vibration. In scanning experiments using mirror-finished aluminum with a curved surface, the position and orientation control errors were sufficiently small in high-speed operation at the limit of the robot arm's performance. Several minute scratches on the mirror-finished aluminum could be detected and their locations were mapped as 3D CAD data.

Fast yet predictable braking manoeuvers for real-time robot control

This paper proposes a framework for generating fast, smooth and predictable braking manoeuvers for a controlled robot. The proposed framework integrates two approaches to obtain feasible modal limits for designing braking trajectories. The first approach is realtime capable but conservative considering the usage of the available feasible actuator control region, resulting in longer braking times. In contrast, the second approach maximizes the used braking control inputs at the cost of requiring more time to evaluate larger, feasible modal limits via optimization. Both approaches allow for predicting the robot's stopping trajectory online. In addition, we also formulated and solved a constrained, nonlinear final-time minimization problem to find optimal torque inputs. The optimal solutions were used as a benchmark to evaluate the performance of the proposed predictable braking framework. A comparative study was compiled in simulation versus a classical optimal controller on a 7-DoF robot arm with only three moving joints. The results verified the effectiveness of our proposed framework and its integrated approaches in achieving fast robot braking manoeuvers with accurate online predictions of the stopping trajectories and distances under various braking settings.

Robotic Raman Spectroscopy for Rapid Fatty Acid Measurement in Salmon Fillets

In this work, we present a robotic solution to measure the content of omega-3 fatty acids in salmon fillets using Raman spectroscopy. Fatty acid composition is a significant quality parameter for the salmon farming industry as a high content contributes to consumer health, a redder fillet, and fewer unwanted dark spots, leading to a higher fillet price. The current methodology for evaluating omega-3 fatty acids in salmon fillets is conducted manually using a Raman probe, which is tiresome, error-prone, time-consuming, and demands labor. To overcome these drawbacks, we propose a semi-autonomous robotic scanning platform composed of a visual servoing system and a motion planning algorithm. We then develop a proof-of-concept demonstration using commercial Raman technology, a 6-DoF robot arm, an RGB camera, and a linear conveyor module, emulating an industrial environment on a laboratory scale. The proposed robot and sensor integration methodology effectively performs real-time measurement of fatty acid content in salmon fillets moving on a conveyor belt at low and high speeds, preventing human-prone errors and increasing operating efficiency.