Abstract
The challenge of synthesizing motion behaviors is a long-standing problem in robotics. With the recent advent of complex humanoid systems, this challenge grows ever demanding. Due to their anthropomorphic design, humanoids should move in a human-like manner to facilitate movement within man-made environments and to accommodate interaction with their biological counterparts. Common control strategies for emulating human motion involve generating joint space trajectories or learning specific motions, but these approaches require off-line computations and do not generalize well to related tasks. There is a pressing need for a framework where natural motion is generated in real-time for a large range of tasks.
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© 2004 Springer Science + Business Media, Inc.
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Khatib, O., Warren, J., De Sapio, V., Sentis, L. (2004). Human-Like Motion from Physiologically-Based Potential Field. In: Jacquart, R. (eds) Building the Information Society. IFIP International Federation for Information Processing, vol 156. Springer, Boston, MA. https://doi.org/10.1007/978-1-4020-8157-6_79
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DOI: https://doi.org/10.1007/978-1-4020-8157-6_79
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Online ISBN: 978-1-4020-8157-6
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