Ian S. Howard
Papers
9
Total Citations
412
H-Index
5
About
Ian S. Howard is a pioneering researcher at the intersection of robotics, haptics, and human motor control. His work centers on designing novel robotic manipulanda—including modular planar systems with end-point torque control and low-cost 3D-printed arms—to investigate how humans learn and represent skillful manipulation. His most-cited paper (234 citations) introduced a modular planar robotic manipulandum that has become a foundational tool in haptics research. Howard’s major contributions include demonstrating that the brain forms multiple, grasp-specific representations of tool dynamics, a finding published in a highly influential 2010 study (70 citations). He has also broken new ground by bringing realistic haptic feedback into virtual moral dilemmas, using a robotic manipulandum and interactive sculpture to simulate moral actions in VR (62 citations). His recent work explores de novo motor learning, showing that task-relevant haptic feedback improves asymptotic performance in controlling novel effectors. Beyond these achievements, Howard’s designs for bimanual haptic interfaces and workspace comparisons have advanced human-robot interaction, while his low-cost, 3D-printed robot arms make this technology more accessible. His research continues to shape our understanding of motor learning and the role of haptics in virtual environments.
Research Focus
Key Achievements
Top Papers
- 1A modular planar robotic manipulandum with end-point torque control234 citations · 2009
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- 4Workspace comparisons of setup configurations for human-robot interaction28 citations · 2010
- 5Design and Kinematic Analysis of a 3D-Printed 3DOF Robotic Manipulandum6 citations · 2023
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- 7Design and Prototyping of a 3DOF Worm-drive Robot Arm3 citations · 2023
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