首页|Findings from Vrije Universiteit Brussel (VUB) Yields New Data on Robotics (Real -time Constraint-based Planning and Control of Robotic Manipulators for Safe Hum an-robot Collaboration)
Findings from Vrije Universiteit Brussel (VUB) Yields New Data on Robotics (Real -time Constraint-based Planning and Control of Robotic Manipulators for Safe Hum an-robot Collaboration)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Robotics is now availab le. According to news reporting out of Brussels, Belgium, by NewsRx editors, res earch stated, “A recent trend in industrial robotics is to have robotic manipula tors working side-by-side with human operators. A challenging aspect of this coe xistence is that the robot is required to reliably solve complex path-planning p roblems in a dynamically changing environment.” Our news journalists obtained a quote from the research from Vrije Universiteit Brussel (VUB), “To ensure the safety of the human operator while simultaneously achieving efficient task realization, this paper introduces a computationally ef ficient planning and control architecture that combines a Rapidly-exploring Rand om Tree (RRT) path planner with a trajectory-based Explicit Reference Governor ( ERG) by means of a reference selector. The resulting scheme can steer the robot arm to the desired end-effector pose in the presence of actuator saturation, lim ited joint ranges, speed limits, a cluttered static obstacle environment, and mo ving human collaborators. The effectiveness of the proposed framework is experim entally validated on the Franka Emika Panda robot arm and fed with feedback info rmation from state-of-the-art depth perception systems. Our method outperforms b oth the standalone RRT and ERG algorithms in cluttered static environments where it overcomes: i) the RRT’s inability to handle dynamic constraints which result in constraint violations and ii) the ERG’s undesirable property of getting trap ped in local minima.”
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