A Nonlinear Model Predictive Control Scheme for Cooperative Manipulation with Singularity and Collision Avoidance

This paper addresses the problem of cooperative transportation of an object rigidly grasped by $N$ robotic agents. In particular, we propose a Nonlinear Model Predictive Control (NMPC) scheme that guarantees the navigation of the object to a desired pose in a bounded workspace with obstacles, while complying with certain input saturations of the agents. Moreover, the proposed methodology ensures that the agents do not collide with each other or with the workspace obstacles as well as that they do not pass through singular configurations. The feasibility and convergence analysis of the NMPC are explicitly provided. Finally, simulation results illustrate the validity and efficiency of the proposed method.Comment: Simulation results with 3 agents adde

Obstacle Avoidance Method for Electric Wheelchairs Based on a Multi-Layered Non-Contact Impedance Model

This paper proposes an obstacle avoidance method based on a multi-layered non-contact impedance model for control of the biosignal-based electric wheelchair. The proposed system can calculate a virtual repulsive force before the collision by multi-layered impedance fields covered around it. This system therefore regulates desired path to avoid obstacles in a variety of situations. In the experiments, the mobile robot passed through obstacles smoothly, and could stop emergently to avoid the obstacle in front of the robot owing to virtual forces calculated by the proposed model.This work was supported by JSPS KAKENHI Grant Number JP26330226

Unlimited-wokspace teleoperation

Thesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2012Includes bibliographical references (leaves: 100-105)Text in English; Abstract: Turkish and Englishxiv, 109 leavesTeleoperation is, in its brief description, operating a vehicle or a manipulator from a distance. Teleoperation is used to reduce mission cost, protect humans from accidents that can be occurred during the mission, and perform complex missions for tasks that take place in areas which are difficult to reach or dangerous for humans. Teleoperation is divided into two main categories as unilateral and bilateral teleoperation according to information flow. This flow can be configured to be in either one direction (only from master to slave) or two directions (from master to slave and from slave to master). In unlimited-workspace teleoperation, one of the types of bilateral teleoperation, mobile robots are controlled by the operator and environmental information is transferred from the mobile robot to the operator. Teleoperated vehicles can be used in a variety of missions in air, on ground and in water. Therefore, different constructional types of robots can be designed for the different types of missions. This thesis aims to design and develop an unlimited-workspace teleoperation which includes an omnidirectional mobile robot as the slave system to be used in further researches. Initially, an omnidirectional mobile robot was manufactured and robot-operator interaction and efficient data transfer was provided with the established communication line. Wheel velocities were measured in real-time by Hall-effect sensors mounted on robot chassis to be integrated in controllers. A dynamic obstacle detection system, which is suitable for omnidirectional mobility, was developed and two obstacle avoidance algorithms (semi-autonomous and force reflecting) were created and tested. Distance information between the robot and the obstacles was collected by an array of sensors mounted on the robot. In the semi-autonomous teleoperation scenario, distance information is used to avoid obstacles autonomously and in the force-reflecting teleoperation scenario obstacles are informed to the user by sending back the artificially created forces acting on the slave robot. The test results indicate that obstacle avoidance performance of the developed vehicle with two algorithms is acceptable in all test scenarios. In addition, two control models were developed (kinematic and dynamic control) for the local controller of the slave robot. Also, kinematic controller was supported by gyroscope

Trajectory Deformations from Physical Human-Robot Interaction

Robots are finding new applications where physical interaction with a human is necessary: manufacturing, healthcare, and social tasks. Accordingly, the field of physical human-robot interaction (pHRI) has leveraged impedance control approaches, which support compliant interactions between human and robot. However, a limitation of traditional impedance control is that---despite provisions for the human to modify the robot's current trajectory---the human cannot affect the robot's future desired trajectory through pHRI. In this paper, we present an algorithm for physically interactive trajectory deformations which, when combined with impedance control, allows the human to modulate both the actual and desired trajectories of the robot. Unlike related works, our method explicitly deforms the future desired trajectory based on forces applied during pHRI, but does not require constant human guidance. We present our approach and verify that this method is compatible with traditional impedance control. Next, we use constrained optimization to derive the deformation shape. Finally, we describe an algorithm for real time implementation, and perform simulations to test the arbitration parameters. Experimental results demonstrate reduction in the human's effort and improvement in the movement quality when compared to pHRI with impedance control alone

Robot-Assisted Navigation for Visually Impaired through Adaptive Impedance and Path Planning

This paper presents a framework to navigate visually impaired people through unfamiliar environments by means of a mobile manipulator. The Human-Robot system consists of three key components: a mobile base, a robotic arm, and the human subject who gets guided by the robotic arm via physically coupling their hand with the cobot's end-effector. These components, receiving a goal from the user, traverse a collision-free set of waypoints in a coordinated manner, while avoiding static and dynamic obstacles through an obstacle avoidance unit and a novel human guidance planner. With this aim, we also present a legs tracking algorithm that utilizes 2D LiDAR sensors integrated into the mobile base to monitor the human pose. Additionally, we introduce an adaptive pulling planner responsible for guiding the individual back to the intended path if they veer off course. This is achieved by establishing a target arm end-effector position and dynamically adjusting the impedance parameters in real-time through a impedance tuning unit. To validate the framework we present a set of experiments both in laboratory settings with 12 healthy blindfolded subjects and a proof-of-concept demonstration in a real-world scenario.Comment: 7 pages, 7 figures, submitted to IEEE International Conference on Robotics and Automation, for associated video, see https://youtu.be/B94n3QjdnJ