The uses of robots are changing from static environments in factories to encompass novel concepts such as human–robot collaboration unstructured settings. Preprogramming all the functionalities for becomes impractical, and hence, need learn how react new events autonomously, just like humans. However, humans, unlike machines, naturally skilled responding unexpected circumstances based on either experiences or observations. Hence, embedding anthropoid behaviors into entails development...

Manipulation in contrast to grasping is a trajectorial task that needs use dexterous hands. Improving the dexterity of robot hands increases controller complexity and thus requires concept postural synergies. Inspired from synergies, this research proposes new framework called kernelized synergies focuses on reusability same subspace for precision manipulation. In work, computed parameterized by movement primitives (KMPs) preserve its manipulation characteristics allows reuse objects. The...

Humans in contrast to robots are excellent performing fine manipulation tasks owing their remarkable dexterity and sensorimotor organization. Enabling acquire such capabilities, necessitates a framework that not only replicates the human behaviour but also integrates multi-sensory information for autonomous object interaction. To address limitations, this research proposes augment previously developed kernelized synergies with visual perception automatically adapt unknown objects. The...

The increasing use of modern power electronics raises the issue harmonics in systems which ultimately deteriorate its optimal performance terms of: increased loss, breaker failure and mal-operation equipment.It has been found that most severe system are odd ones due to their unsymmetrical nature.This work presents new framework for estimation classification using machine learning approaches.Initially, a shallow neural network fuzzy logic used estimate contents voltage currents signals.Based...

In recent years Sim2Real approaches have brought great results to robotics. Techniques such as model-based learning or domain randomization can help overcome the gap between simulation and reality, but in some situations accuracy is still needed. An example agricultural robotics, which needs detailed simulations, both terms of dynamics visuals. However, software not capable quality accuracy. Current techniques are helpful mitigating problem, for these specific tasks they enough.

Manipulation in contrast to grasping is a trajectorial task that needs use dexterous hands. Improving the dexterity of robot hands, increases controller complexity and thus requires concept postural synergies. Inspired from synergies, this research proposes new framework called kernelized synergies focuses on re-usability same subspace for precision manipulation. In work, computed synergies; parameterized by probabilistic movement primitives, treated with kernel preserve its manipulation...

Designing robotic tasks for co-manipulation necessitates to exploit not only proprioceptive but also exteroceptive information improved safety and autonomy. Following such instinct, this research proposes formulate intuitive following human viewpoint by incorporating visuo-tactile perception. The visual data using depth cameras surveils determines the object dimensions intentions while tactile sensing ensures maintain desired contact avoid slippage. Experiment performed on robot platform...

Handling non-rigid objects using robot hands necessities a framework that does not only incorporate human-level dexterity and cognition but also the multi-sensory information system dynamics for robust fine interactions. In this research, our previously developed kernelized synergies framework, inspired from human behaviour on reusing same subspace grasping manipulation, is augmented with visuo-tactile perception autonomous flexible adaptation to unknown objects. To detect estimate their...

High-fidelity datasets play a pivotal role in imbuing simulators with realism, enabling the benchmarking of various state-of-the-art deep inference models. These models are particularly instrumental tasks such as semantic segmentation, classification, and localization. This study showcases efficacy customized manufacturing dataset comprising 60 classes creation high-fidelity digital twin robotic manipulation environment. By leveraging concept transfer learning, different 6D pose estimation...

Humans in contrast to robots are excellent performing fine manipulation tasks owing their remarkable dexterity and sensorimotor organization. Enabling acquire such capabilities, necessitates a framework that not only replicates the human behaviour but also integrates multi-sensory information for autonomous object interaction. To address limitations, this research proposes augment previously developed kernelized synergies with visual perception automatically adapt unknown objects. The...

Pruning is the art of cutting unwanted and unhealthy plant branches one difficult tasks in field robotics. It becomes even more complex when are moving. Moreover, reproducibility robot pruning skills another challenge to deal with due heterogeneous nature vines vineyard. This research proposes a multi-modal framework dynamic aim sim2real skill transfer. The 3D models constructed blender engine rendered simulated environment as need for training robot. Natural Admittance Controller (NAC)...

The uses of robots are changing from static environments in factories to encompass novel concepts such as Human-Robot Collaboration unstructured settings. Pre-programming all the functionalities for becomes impractical, and hence, need learn how react new events autonomously, just like humans. However, humans, unlike machines, naturally skilled responding unexpected circumstances based on either experiences or observations. Hence, embedding anthropoid behaviours into entails development...

Enabling robots to work in close proximity humans necessitates a control framework that does not only incorporate multi-sensory information for autonomous and coordinated interactions but also has perceptive task planning ensure an adaptable flexible collaborative behaviour. In this research, intuitive stack-of-tasks (iSoT) formulation is proposed, defines the robot's actions by considering human-arm postures progression. The augmented with visuo-tactile effectively perceive environment...