The efficiency and productivity benefits of robotic manipulation allows for the expansion of its application scope, which currently spans across factories, medical, pharmaceutical, biological and operational services. Present day robotic manipulation research addresses issues such as mobile manipulation in poorly modeled environments, learning, adaptation, the development of real-world manipulation, emulation of human-like behavior, human-robot interaction as well as cooperation, and design of forced controlled and compliant manipulators.
New research from Frost & Sullivan (ti.frost.com), Emerging Trends in Robotic Manipulation, finds a renewed interest in robotic manipulation, especially with the increasing uncertainties and complexities of the real world. In manipulation, an important robotics research area, the focus is now slowly moving toward developing remote manipulators.
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Currently the focus has begun to slowly shift toward developing remote manipulators in the research area of robotic manipulation. At the same time, the industry continues to work toward improving robotic manipulator end effectors dexterity, and minimizing or reducing the number of configuration parameters without compromising precision positioning with distributed manipulation.
"Perception-based learning for robotic manipulation tasks involving the use of force/torque sensors represents a hot area wherein qualitative spatial reasoning is done from a bottom-up perspective," notes Frost and Sullivan Research Analyst Vishnu Sivadevan. "Much work has also been done on intelligent robotic motion using sensory input for flexible manufacturing cells."
The world’s first magnetic resonance imaging (MRI)-compatible surgical robot, ‘NeuroArm,’ represents a notable advancement in the field of robotic manipulation. Performing a surgery requires enhanced spatial resolution to view the parts at a cellular level rather than just the organ level. The newly developed surgical robot meets these enhanced spatial resolution requirements and could also assist with operative medicine as well as surgeries.
Despite such advances, there still remain significant technological challenges related to improving manipulation skills such as hand-eye coordination, transport, alignment, and grasping.
"The robotic visual servoing system, which refers to the use of visual feedback for coordinated movements of a robotic arm, uses only image-based two-dimensional feature tracking," says Sivadevan. "On the other hand, the human system takes into account the three-dimensional features of the environment. Thus, the visually guided grasp mechanism exhibited in humans requires observance and understanding of three-dimensional features and not just two-dimensional geometric features."
Going forward, powerful computers will control the next generation of robots. A number of promising new technologies such as neural networks, artificial intelligence, fuzzy reasoning, and many other techniques will find their applicability. Thus, research should focus on developing algorithms and automatic planners for robotic manipulators. Moreover, research on articulated arm design, end effectors design and kinematics, as well as behavior-based design of robot effectors needs further study and funding.
Emerging Trends in Robotic Manipulation is part of the Technical Insights Growth Partnership Service, which also includes the following research services: Impact Analysis of MEMS based Sensors & Actuators on Industrial Automation, Developments in Sensor Interfaces, and Developments in Motion Detection Sensors. All research services included in subscriptions provide detailed technology trends, evaluated following extensive interviews with market participants. Interviews with the press are available.
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