Supervised Autonomous Locomotion and Manipulation for Disaster Response with a Centaur-like Robot

Mobile manipulation tasks are one of the key challenges in the field of search and rescue (SAR) robotics requiring robots with flexible locomotion and manipulation abilities. Since the tasks are mostly unknown in advance, the robot has to adapt to a wide variety of terrains and workspaces during a mission. The centaur-like robot Centauro has a hybrid legged-wheeled base and an anthropomorphic upper body to carry out complex tasks in environments too dangerous for humans. Due to its high number of degrees of freedom, controlling the robot with direct teleoperation approaches is challenging and exhausting. Supervised autonomy approaches are promising to increase quality and speed of control while keeping the flexibility to solve unknown tasks. We developed a set of operator assistance functionalities with different levels of autonomy to control the robot for challenging locomotion and manipulation tasks. The integrated system was evaluated in disaster response scenarios and showed promising performance.Comment: In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 201

Planning and Real Time Control of a Minimally Invasive Robotic Surgery System

This paper introduces the planning and control software of a teleoperating robotic system for minimally invasive surgery. It addresses the problem of how to organize a complex system with 41 degrees of freedom including robot setup planning, force feedback control and nullspace handling with three robotic arms. The planning software is separated into sequentially executed planning and registration procedures. An optimal setup is first planned in virtual reality and then adapted to variations in the operating room. The real time control system is composed of hierarchical layers. The design is flexible and expandable without losing performance. Structure, functionality and implementation of planning and control are described. The robotic system provides the surgeon with an intuitive hand-eye-coordination and force feedback in teleoperation for both hands

Aerial-Ground collaborative sensing: Third-Person view for teleoperation

Rapid deployment and operation are key requirements in time critical application, such as Search and Rescue (SaR). Efficiently teleoperated ground robots can support first-responders in such situations. However, first-person view teleoperation is sub-optimal in difficult terrains, while a third-person perspective can drastically increase teleoperation performance. Here, we propose a Micro Aerial Vehicle (MAV)-based system that can autonomously provide third-person perspective to ground robots. While our approach is based on local visual servoing, it further leverages the global localization of several ground robots to seamlessly transfer between these ground robots in GPS-denied environments. Therewith one MAV can support multiple ground robots on a demand basis. Furthermore, our system enables different visual detection regimes, and enhanced operability, and return-home functionality. We evaluate our system in real-world SaR scenarios.Comment: Accepted for publication in 2018 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR

A Tele-Operated Display With a Predictive Display Algorithm

Tele-operated display systems with head mounted displays (HMD) are becoming popular as visual feedback systems for tele-operation systems. However, the users are suffered from time-varying bidirectional delays caused by the latency and limited bandwidth of wireless communication networks. Here, we develop a tele-operated display system and a predictive display algorithm allowing comfortable use of HMDs by operators of tele-operation systems. Inspired by the kinematic model of the human head-neck complex, we built a robot neck-camera system to capture the field of view in any desired orientation. To reduce the negative effects of the time-varying bidirectional communication delay and operation delay of the robot neck, we developed a predictive display algorithm based on a kinematic model of the human/robot neck-camera system, and a geometrical model of a camera. Experimental results showed that the system provide predicted images with high frame rate to the user

Passivity-Based Control of Human-Robotic Networks with Inter-Robot Communication Delays and Experimental Verification

In this paper, we present experimental studies on a cooperative control system for human-robotic networks with inter-robot communication delays. We first design a cooperative controller to be implemented on each robot so that their motion are synchronized to a reference motion desired by a human operator, and then point out that each robot motion ensures passivity. Inter-robot communication channels are then designed via so-called scattering transformation which is a technique to passify the delayed channel. The resulting robotic network is then connected with human operator based on passivity theory. In order to demonstrate the present control architecture, we build an experimental testbed consisting of multiple robots and a tablet. In particular, we analyze the effects of the communication delays on the human operator's behavior

Implementation and design of a teleoperation system based on a VMEBUS/68020 pipelined architecture

A pipelined control design and architecture for a force-feedback teleoperation system that is being implemented at the Jet Propulsion Laboratory and which will be integrated with the autonomous portion of the testbed to achieve share control is described. At the local site, the operator sees real-time force/torque displays and moves two 6-degree of freedom (dof) force-reflecting hand-controllers as his hands feel the contact force/torques generated at the remote site where the robots interact with the environment. He also uses a graphical user menu to monitor robot states and specify system options. The teleoperation software is written in the C language and runs on MC68020-based processor boards in the VME chassis, which utilizes a real-time operating system; the hardware is configured to realize a four-stage pipeline configuration. The environment is very flexible, such that the system can easily be configured as a stand-alone facility for performing independent research in human factors, force control, and time-delayed systems

Autonomy Infused Teleoperation with Application to BCI Manipulation

Robot teleoperation systems face a common set of challenges including latency, low-dimensional user commands, and asymmetric control inputs. User control with Brain-Computer Interfaces (BCIs) exacerbates these problems through especially noisy and erratic low-dimensional motion commands due to the difficulty in decoding neural activity. We introduce a general framework to address these challenges through a combination of computer vision, user intent inference, and arbitration between the human input and autonomous control schemes. Adjustable levels of assistance allow the system to balance the operator's capabilities and feelings of comfort and control while compensating for a task's difficulty. We present experimental results demonstrating significant performance improvement using the shared-control assistance framework on adapted rehabilitation benchmarks with two subjects implanted with intracortical brain-computer interfaces controlling a seven degree-of-freedom robotic manipulator as a prosthetic. Our results further indicate that shared assistance mitigates perceived user difficulty and even enables successful performance on previously infeasible tasks. We showcase the extensibility of our architecture with applications to quality-of-life tasks such as opening a door, pouring liquids from containers, and manipulation with novel objects in densely cluttered environments