Dynamic movement primitives-based human action prediction and shared control for bilateral robot teleoperation

This article presents a novel shared-control teleoperation framework that integrates imitation learning and bilateral control to achieve system stability based on a new dynamic movement primitives (DMPs) observer. First, a DMPs-based observer is first created to capture human operational skills through offline human demonstrations. The learning results are then used to predict human action intention in teleoperation. Compared with other observers, the DMPs-based observer incorporates human operational features and can predict long-term actions with minor errors. A high-gain observer is established to monitor the robot’s status in real time on the leader side. Subsequently, two controllers on both the follower and leader sides are constructed based on the outputs of the observers. The follower controller shares control authorities to address accidents in real-time and correct prediction errors of the observation using delayed leader commands. The leader controller minimizes position-tracking errors through force feedback. The convergence of the predictions of the DMPs-based observer under the time delays and teleoperation system stability are proved by building two Lyapunov functions. Finally, two groups of comparative experiments are conducted to verify the advantages over other methods and the effectiveness of the proposed framework in motion prediction with time delays and obstacle avoidance

A Topology of Shared Control Systems—Finding Common Ground in Diversity

Shared control is an increasingly popular approach to facilitate control and communication between humans and intelligent machines. However, there is little consensus in guidelines for design and evaluation of shared control, or even in a definition of what constitutes shared control. This lack of consensus complicates cross fertilization of shared control research between different application domains. This paper provides a definition for shared control in context with previous definitions, and a set of general axioms for design and evaluation of shared control solutions. The utility of the definition and axioms are demonstrated by applying them to four application domains: automotive, robot-assisted surgery, brain–machine interfaces, and learning. Literature is discussed for each of these four domains in light of the proposed definition and axioms. Finally, to facilitate design choices for other applications, we propose a hierarchical framework for shared control that links the shared control literature with traded control, co-operative control, and other human–automation interaction methods. Future work should reveal the generalizability and utility of the proposed shared control framework in designing useful, safe, and comfortable interaction between humans and intelligent machines

The Effect of Trial-by-trial Adaptation on Conflicts in Haptic Shared Control for Free-Air Teleoperation Tasks

Haptic shared control can improve execution of teleoperation and driving tasks. However, shared control designs may suffer from conflicts between individual human operators and constant haptic assistance when their desired trajectories differ, leading to momentarily increased forces, discomfort or even deteriorated performance. This study investigates ways to reduce conflicts between individual human operators and a haptic shared controller by modifying supported trajectories. Subjects (n=12) performed a repetitive movement task in an abstract environment with varying spatio-temporal constraints, both during manual control and while supported by haptic shared control. Four types of haptic shared control were compared, combining two design properties: the initial supported trajectory (either the centerline of the environment or an individualized trajectory based on manual control trials), and trial-by-trial adaptation of guidance towards previously performed trajectories (either present or absent). Trial-by-trial adaptation of guidance reduced conflicts compared to non-adaptive guidance, whether the initial trajectory was individualized or not. Without trial-by-trial adaptation, individualized trajectories also reduced conflicts, but not completely: when guided, operators adapt their preferred trajectories. In conclusion, trial-by-trial adaptation is the most promising approach to mitigate conflicts during repetitive motion tasks

The effect of trial-by-trial adaptation on conflicts in haptic shared control for free-air teleoperation tasks

\u3cp\u3eHaptic shared control can improve execution of teleoperation and driving tasks. However, shared control designs may suffer from conflicts between individual human operators and constant haptic assistance when their desired trajectories differ, leading to momentarily increased forces, discomfort, or even deteriorated performance. This study investigates ways to reduce conflicts between individual human operators and a haptic shared controller by modifying supported trajectories. Subjects (n=12) performed a repetitive movement task in an abstract environment with varying spatio-temporal constraints, both during manual control and while supported by haptic shared control. Four types of haptic shared control were compared, combining two design properties: the initial supported trajectory (either the centerline of the environment or an individualized trajectory based on manual control trials), and trial-by-trial adaptation of guidance towards previously performed trajectories (either present or absent). Trial-by-trial adaptation of guidance reduced conflicts compared to non-adaptive guidance, whether the initial trajectory was individualized or not. Without trial-by-trial adaptation, individualized trajectories also reduced conflicts, but not completely: when guided, operators adapt their preferred trajectories. In conclusion, trial-by-trial adaptation is the most promising approach to mitigate conflicts during repetitive motion tasks.\u3c/p\u3

Decrypting the multi-functional biological activators and inducers of defense responses against biotic stresses in plants

Plant diseases are still the main problem for the reduction in crop yield and a threat to global food security. Additionally, excessive usage of chemical inputs such as pesticides and fungicides to control plant diseases have created another serious problem for human and environmental health. In view of this, the application of plant growth-promoting rhizobacteria (PGPR) for controlling plant disease incidences has been identified as an eco-friendly approach for coping with the food security issue. In this review, we have identified different ways by which PGPRs are capable of reducing phytopathogenic infestations and enhancing crop yield. PGPR suppresses plant diseases, both directly and indirectly, mediated by microbial metabolites and signaling components. Microbial synthesized anti-pathogenic metabolites such as siderophores, antibiotics, lytic enzymes, hydrogen cyanide, and several others act directly on phytopathogens. The indirect mechanisms of reducing plant disease infestation are caused by the stimulation of plant immune responses known as initiation of systemic resistance (ISR) which is mediated by triggering plant immune responses elicited through pathogen-associated molecular patterns (PAMPs). The ISR triggered in the infected region of the plant leads to the development of systemic acquired resistance (SAR) throughout the plant making the plant resistant to a wide range of pathogens. A number of PGPRs including Pseudomonas and Bacillus genera have proven their ability to stimulate ISR. However, there are still some challenges in the large-scale application and acceptance of PGPR for pest and disease management. Further, we discuss the newly formulated PGPR inoculants possessing both plant growth-promoting activities and plant disease suppression ability for a holistic approach to sustaining plant health and enhancing crop productivity