Omnidirectional Robot Platform Research Articles

Targeted Sampling Dynamic Window Approach: A Path-Aware Dynamic Window Approach Sampling Strategy for Omni-Directional Robots

Abstract This paper describes a sampling strategy for the dynamic window approach (DWA), a local path planner, for omni-directional robot motion planning. An efficient local planner allows the robot to quickly respond to dynamic obstacles and ensures that commanded velocities meet the dynamic constraints of the robot. While typical DWA implementations sample the velocity space evenly, we propose that targeted sampling (TS) will result in a more fine-grained search of the relevant velocity space, leading to better control and performance in space-constrained environments. Our TS-DWA strategy is informed by the global planned path, allowing us to sample more velocities in the general path direction. We employ a polar velocity generator to selectively sample velocities and couple angular velocity samples to the path curvature. A bias for angular velocity is added for robots with a preferred heading, such as robots with forward-mounted sensors, to quickly turn toward the desired direction for better sensing. The strategy is implemented as a robot operating system (ROS) navigation stack local_planner plugin and tested in simulation with Gazebo using an omni-directional robot platform. Experiments show that as the space around the simulated robot gets smaller, our proposed sampling strategy results in more successful navigation trials to the goal in space-constrained environments compared to other commonly used methods like DWA and timed-elastic-band, where planning fails or oscillates. TS-DWA was also deployed on the Vision60 quadrupedal robot to demonstrate navigation through narrow corridors in the real world.

Kinematic and optimal design of a three-wheeled holonomic omnidirectional robot platform for mobile manipulation tasks

Mobile manipulator robots are increasingly vital in industrial and service sectors, serving roles in assembly, inspection, and hazardous environments. The integration of a manipulator with a mobile robot base imposes unique demands on the vehicle's drive system. This paper introduces a three-wheel holonomic omnidirectional robot designed for mobile applications. It explores kinematic equations, electronic integration, and mechanical design for holonomic motion. This platform excels in mobility, capable of simultaneous translation and rotation, facilitating precise multidirectional motion. Its equilateral truncated triangular structure ensures stability, supporting up to 4 kg. With three omnidirectional wheels and DC motors, controlled by EMS 30A H-Bridge and Arduino Mega 2560, it offers an open platform for research and development. This robust platform aligns kinematic calculations with mathematical models, promising efficiency for diverse mobile manipulation robot applications.

OBoat: An Agile Omnidirectional Robotic Platform for Unmanned Surface Vehicle Tasks

OBoat: An Agile Omnidirectional Robotic Platform for Unmanned Surface Vehicle Tasks

Human-Centered Navigation and Person-Following with Omnidirectional Robot for Indoor Assistance and Monitoring

Robot assistants and service robots are rapidly spreading out as cutting-edge automation solutions to support people in their everyday life in workplaces, health centers, and domestic environments. Moreover, the COVID-19 pandemic drastically increased the need for service technology to help medical personnel in critical conditions in hospitals and domestic scenarios. The first requirement for an assistive robot is to navigate and follow the user in dynamic environments in complete autonomy. However, these advanced multitask behaviors require flexible mobility of the platform to accurately avoid obstacles in cluttered spaces while tracking the user. This paper presents a novel human-centered navigation system that successfully combines a real-time visual perception system with the mobility advantages provided by an omnidirectional robotic platform to precisely adjust the robot orientation and monitor a person while navigating. Our extensive experimentation conducted in a representative indoor scenario demonstrates that our solution offers efficient and safe motion planning for person-following and, more generally, for human-centered navigation tasks.

Evaluation of Velocity and Acceleration Effect on Mecanum Wheel Robot Positioning

In this paper, a Mecanum wheel omnidirectional robotic platform made for taking measurements in harsh and dangerous conditions is introduced. Due to the necessity of highly accurate displacement of the platform for measuring the conditions at the exact measurement point and due to known Mecanum wheel slippage and relatively poor position accuracy, a calibration procedure for minimizing positioning error had to be implemented. For this task, a highly accurate stereographic digital image correlation (DIC) system was used to measure platform displacement. A series of parameters, namely linear maximum velocity and acceleration/deceleration values, were taken into account during the calibration procedure to find the best combination allowing precise movement of the robot. It was found that low acceleration values were the main causes of the robot’s poor positioning accuracy and could cause the robot’s motors to stall. Max speed values proved to have little effect on the robot’s positioning.

Experimental demonstration and modeling of a robotic neutron detector with spectral and directional sensitivity for treaty verification

International safeguards and arms control agreements often require labor-intensive, intrusive onsite inspections to perform verification tasks. The ability to localize a neutron source and/or characterize a neutron field may be imperative for identifying anomalies. We are interested in the role of autonomous mobile robots, which, if designed properly, may be more effective and efficient and less intrusive than their human counterparts. Toward developing such a capability, we have constructed the N-SpecDir Bot, comprised of three boron-coated straw detectors azimuthally-distributed within a cylinder of high-density polyethylene, which is mounted on an omni-directional robotic platform. Our N-SpecDir Bot is specifically designed to provide spectral and directional sensitivity, in addition to gross counts, by utilizing the signals from the three detectors. The detection system has been extensively characterized by MCNP modeling, which has been benchmarked to experiments conducted at the Princeton Plasma Physics Laboratory. We demonstrate the spectral and directional sensitivity experimentally and in simulation, and provide a simple yet robust method for directional measurements.

An Omnidirectional Platform for Education and Research in Cooperative Robotics

In this paper we present a new, affordable, omnidirectional robot platform which is suitable for research and education in cooperative robotics. We design and implement the platform for the purpose of multi-agent object manipulation and transportation. The design consists of three omnidirectional wheels with two additional traction wheels, making multirobot object manipulation possible. It is validated by performing simple experiments using a setup with one robot and one target object. The execution flow of a simple task (Approach–Press–Lift–Hold–Set) is studied. In addition, we experiment to find the limits of the applied pressure and object orientation under certain conditions. The experiments demonstrate the significance of our inexpensive platform for research and education by proving its feasibility of use in topics such as collaborative robotics, physical interaction, and mobile manipulation.

Omnidirectional Robotic Platform for Surveillance of Particle Accelerator Environments with Limited Space Areas

Intelligent robotic systems are becoming essential for inspections and measurements in harsh environments. This article presents the design of an omnidirectional robotic platform for tunnel inspection with spatial limitations. This robot was born from the need to automate the surveillance process of the Super Proton Synchrotron (SPS) accelerator of the European Organization for Nuclear Research (CERN), where there is remaining radiation. The accelerator is located within a tunnel that is divided by small doors of 400 × 200 mm dimensions, through which the robot has to cross. The designed robot brings a robotic arm, and the needed devices to carry out the inspection. Thanks to this design, the robot application may vary by replacing certain devices and tools. In addition, this paper presents the kinematic and dynamic control models for the robotic platform.

High mobility control of an omnidirectional platform for gait rehabilitation after stroke.

We present a novel control method for an omnidirectional robotic platform for gait training. This mobile platform or "walker" provides trunk support and allows unrestricted motion of the pelvis simultaneously. In addition to helping the user maintain balance and preventing falls, the walker combines two types of therapeutic intervention: forward propulsion of the trunk and partial body weight support (BWS). The core of the walker's control is an admittance controller that maximizes the platform's horizontal mobility by optimizing the virtual mass of the admittance model. Said mass represents the best tradeoff between a low-frequency oscillation mode that becomes more damped as the virtual mass decreases, and a high-frequency mode that becomes less damped simultaneously and hence could destabilize the system. Forward propulsion of the trunk is aided by a horizontal force that is modulated with the patient's gait speed and turning rate to ensure easy adaptation. BWS is provided by a second, independent admittance controller that generates a spring-like upward force. In an initial study, a stroke patient was able to walk stably in the platform, as evidenced by the absence of oscillations associated with an excessively low virtual mass. A progressive increase in the patient's self-selected speed, along with greater uniformity in the instantaneous velocity, suggest that forward propulsion was effective in compensating the patient's own propulsion deficit.

Robot-Based Training for People With Mild Cognitive Impairment

Current research suggests that physical activity has positive effects on the overall state of people with mild cognitive impairment (MCI) and that the use of new technologies could help those people to keep and improve their postural control and motor skills. In a pilot study, we investigated the use of a device based on a mobile robot for the motor activation of people with MCI, with the goal of investigating the possible influence of such an activity on the cognitive level. The device is an omnidirectional robot platform with handlebars and an integrated force-torque sensor to enable direct interaction with a user. A passive interaction controller with high-level interaction modes for training scenarios is developed. The device and the training are evaluated with ten participants (eight males and two females) from 66 to 78 years of age with MCI in five 1-h sessions. Here, we present the data gathered with the device and the evaluation of the user experience. The results for the precision of controlling the device and the time performance show that the users got better during the training week for most tasks. The participants felt safe during the training and managed to adapt to changes in the device's high-level behavior. Overall, the current results suggest that the proposed training is feasible and the device is suitable for the training. Future work will evaluate pre- and post-training MRI data and data from neuropsychological and memory testing to investigate impacts of the training with the robotic device on the cognitive level of a user.

Consistent triangulation for mobile robot localization using discontinuous angular measurements

Localization is a fundamental operation for the navigation of mobile robots. The standard localization algorithms fuse external measurements of the environment with the odometric evolution of the robot pose to obtain its optimal estimation. In this work, we present a different approach to determine the pose using angular measurements discontinuously obtained in time. The presented method is based on an Extended Kalman Filter (EKF) with a state-vector composed of the external angular measurements. This algorithm keeps track of the angles between actual measurements from robot odometric information. This continuous angular estimation allows the consistent use of the triangulation methods to determine the robot pose at any time during its motion. The article reports experimental results that show the localization accuracy obtained by means of the presented approach. These results are compared to the ones obtained applying the EKF algorithm with the standard pose state-vector. For the experiments, an omnidirectional robotic platform with omnidirectional wheels is used.