Distributed Trajectory Generation for Cooperative Multi-Arm Robots via Virtual Force Interactions

A trajectory generation method for multi-arm robotsthrough cooperative and competitive interactions among multipleend-effectors is proposed. The method can generate the trajectories ofthe multiple arms in a distributed manner based on a concept of a virtualinteraction force which represents an interaction between an end-effectorand an environment. It is shown that the method is effective not only forsimple cooperative tasks such as positioning a common object, but alsofor more complicated tasks including relative motions among arms

Modeling and Control of Multi-Arm and Multi-Leg Robots: Compensating for Object Dynamics during Grasping

Dehio N, Smith J, Wigand DL, et al. Modeling & Control of Multi-Arm and Multi-Leg Robots: Compensating for Object Dynamics during Grasping. In: IEEE/RSJ Int. Conf. on Robotics and Automation. 2018

Virtual Coordination in Collective Object Manipulation

Inspired by nature, swarm robotics aims to increase system robustness while utilizing simple agents. In this work, we present a novel approach to achieve decentralized coordination of forces during collective manipulation tasks resulting in a highly scalable, versatile, and robust solution. In this approach, each robot involved in the collective object manipulation task relies on the behavior of a cooperative ``virtual teammate\u27 in a fully decentralized architecture, regardless of the size and configuration of the real team. By regulating their actions with their corresponding virtual counterparts, robots achieve continuous pose control of the manipulated object, while eliminating the need for inter-agent communication or a leader-follower architecture. To experimentally study the scalability, versatility, and robustness of the proposed collective object manipulation algorithm, a new swarm agent, Δρ is introduced which is able to apply linear forces in any planar direction. Efficiency and effectiveness of the proposed decentralized algorithm are investigated by quantitative performance metrics of settling time, steady-state error, path efficiency, and object velocity profiles in comparison with a force-optimal centralized version that requires complete information. Employing impedance control during manipulation of an object provides a mean to control its dynamic interactions with the environment. The proposed decentralized algorithm is extended to achieve a desired multi-dimensional impedance behavior of the object during a collective manipulation without inter-agent communication. The proposed algorithm extension is built upon the concept of ``virtual coordination\u27 which demands every agent to locally coordinate with one virtual teammate. Since the real population of the team is unknown to the agents, the resultant force applied to the manipulated object would be directly scaled with the team population. Although this scaling effect proves useful during position control of the object, it leads to a deviation from the desired dynamic response when employed in an impedance control scheme. To minimize such deviations, a gradient descent algorithm is implemented to determine a scaling parameter defined on the control action. The simulation results of a multi-robot system with different populations and formations verify the effectiveness of the proposed method in both generating the desired impedance response and estimating the population of the group. Eventually, as two case studies, the introduced algorithm is used in robotic collective manipulation and human- assistance scenarios. Simulation and experimental results indicate that the proposed decentralized communication- free algorithm successfully performs collective manipulation in all tested scenarios, and matches the performance of the centralized controller for increasing number of agents, demonstrating its utility in communication- limited systems, remote environments, and access-limited objects

Safety-Aware Human-Robot Collaborative Transportation and Manipulation with Multiple MAVs

Human-robot interaction will play an essential role in various industries and daily tasks, enabling robots to effectively collaborate with humans and reduce their physical workload. Most of the existing approaches for physical human-robot interaction focus on collaboration between a human and a single ground robot. In recent years, very little progress has been made in this research area when considering aerial robots, which offer increased versatility and mobility compared to their grounded counterparts. This paper proposes a novel approach for safe human-robot collaborative transportation and manipulation of a cable-suspended payload with multiple aerial robots. We leverage the proposed method to enable smooth and intuitive interaction between the transported objects and a human worker while considering safety constraints during operations by exploiting the redundancy of the internal transportation system. The key elements of our system are (a) a distributed payload external wrench estimator that does not rely on any force sensor; (b) a 6D admittance controller for human-aerial-robot collaborative transportation and manipulation; (c) a safety-aware controller that exploits the internal system redundancy to guarantee the execution of additional tasks devoted to preserving the human or robot safety without affecting the payload trajectory tracking or quality of interaction. We validate the approach through extensive simulation and real-world experiments. These include as well the robot team assisting the human in transporting and manipulating a load or the human helping the robot team navigate the environment. To the best of our knowledge, this work is the first to create an interactive and safety-aware approach for quadrotor teams that physically collaborate with a human operator during transportation and manipulation tasks.Comment: Guanrui Li and Xinyang Liu contributed equally to this pape

Cooperative impedance control with time-varying stiffness

The focus of much automation research has been to design controllers and robots that safely interact with the environment. One approach is to use impedance control to specify a relationship between a robot\u27s motion and force and control a grasped object\u27s apparent stiffness, damping, and inertia. Conventional impedance control practices have focused on position-based manipulators - which are inherently non-compliant - using constant, task-dependent impedances. In the event of large trajectory tracking errors, this implementation method generates large interaction forces that can damage the workcell. Additionally, these position-based devices require dedicated force/torque sensors to measure and apply forces. In this paper, we present an alternative impedance controller implemented on cooperating torque-based manipulators. Through the use of time-varying impedance parameters, this controller limits the interaction forces to ensure harmless manipulation. Successful completion of transport and insertion tasks demonstrated the effectiveness of the controller

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

Becoming Human with Humanoid

Nowadays, our expectations of robots have been significantly increases. The robot, which was initially only doing simple jobs, is now expected to be smarter and more dynamic. People want a robot that resembles a human (humanoid) has and has emotional intelligence that can perform action-reaction interactions. This book consists of two sections. The first section focuses on emotional intelligence, while the second section discusses the control of robotics. The contents of the book reveal the outcomes of research conducted by scholars in robotics fields to accommodate needs of society and industry