A Reconfigurable Dual-Opposition Architecture for Single-Hand Assembly and Manipulation
Authors: William Su, Yunosuke Nakamura, Yixiao Wang, Yitong Li, Mingrui Yu, Huanan Qi, Boyuan Liang, Masayoshi Tomizuka, +1 more
Organizations: Aerospace Engineering Program, University of California, Berkeley, Berkeley, CA 94720, USA. · Department of Mechanical Engineering, University of California, Berkeley, Berkeley, CA 94720, USA. · Department of Mechanical Engineering, National University of Singapore, Singapore 117575.
In-hand assembly is constrained by the need to maintain grasps on two separate parts while controlling their relative motion within a single hand. To enable both in-hand assembly and manipulation, we present a reconfigurable dual-opposition architecture. Specifically, to support simultaneous grasping of two parts and coordinated in-hand manipulation, four independently actuated fingers are organized into two virtual finger (VF) oppositions, with their relative configuration controlled by a reconfigurable palm. To describe hand motion and simultaneous two-object grasping configurations, a kinematic model of the fingers and palm and an object-size-conditioned workspace formulation are built. To further evaluate motion performance and assembly capability, finger-joint motion and palm tracking are characterized, and in-hand assembly is demonstrated through tasks involving grasping, alignment, fastening, and pressing. Ablation experiments further demonstrate the importance of finger abduction/adduction and palm reconfiguration for successful in-hand assembly. In simulation, the proposed hand achieves a mean continuous sphere rotation success rate of 98.6% over diameters of 40-230 mm, compared with 73.8% for the LEAP Hand. After policy fine-tuning with external disturbances, the proposed hand achieves 92.8% success under disturbances from multiple directions, compared with 45.2% for the LEAP Hand. Hardware demonstrations further show in-hand rotation of objects of different sizes using policies trained in simulation. Together, these results show that the proposed architecture supports both assembly of two separately held parts and coordinated manipulation of a single object within one hand.
Figures & tables
Fig. 1: Grasp organization in bimanual and single-hand configurations. (a) Two anthropomorphic hands form the oppositions VF A ↔ VF C and VF B ↔ VF D, respectively. (b) The proposed hand realizes this grasp organization with two VF oppositions integrated within one hand. Palm translation adjusts their relative position. (c) Schematic mapping from inter-hand coordination to intra-hand reconfiguration.
Fig. 2: Mechanical design of the proposed 17-DOF reconfigurable hand. (a) The proposed hand mounted on a FANUC CRX-10iA robot arm. (b) Reconfigurable palm mechanism with potentiometer-based position feedback. (c) Finger kinematics showing the four degrees of freedom of each finger, including MCP flexion, PIP flexion, DIP flexion, and MCP abduction/adduction, together with their corresponding motion ranges. (d) Exploded view of the hand.
Capability
Parallel Gripper
Dexterous Hand
Proposed Hand
VF oppositions
Single
Typically single
Dual
Local dexterity
Low
High
High
Two-object adjustment
Limited
Limited
Supported
Relative object motion
Limited
Limited
Supported
In-hand assembly
Limited
Limited
Supported
TABLE I: Comparison of functional capabilities among conventional parallel grippers, dexterous hands, and the proposed hand.
Fig. 3: Sampled workspace for simultaneous two-object grasping. Each accepted hand configuration contributes one sphere center for each VF opposition, with color indicating sphere diameter. The top view shows the largest equal sphere diameter accepted in each spatial bin.
Fig. 4: Hardware characterization of the integrated hand. (a) Commanded joint ranges and encoder measurements; error bars indicate endpoint standard deviations over five cycles. (b) Commanded angle, encoder feedback, tracking error, and motor current for the MCP abduction/adduction joint of finger A. (c) Commanded palm position, potentiometer feedback, and tracking error during extension and retraction.
Fig. 5: Teleoperated assembly demonstrations using the VF A ↔ VF C and VF B ↔ VF D oppositions. Each row shows a task sequence progressing from left to right. (a) Through-wall fastening, with one opposition holding the nut while the other drives the screw from the opposite side. (b) Simultaneously fastening two screws at different spacings using palm reconfiguration. (c) Aligning and fitting a cap onto a glue-stick body. (d) Actuating a syringe by holding the barrel with one opposition and driving the plunger with the other. (e) Routing a cable through an opening with grasp transfer between the two virtual-finger oppositions.
Task
Full hand
MCP abduction/ adduction locked
Fixed palm
Through-wall fastening
✓
✓
×
Simultaneous screw fastening
✓
×
×
Glue-stick capping
✓
×
×
Syringe actuation
✓
✓
×
Cable routing
✓
✓
✓
TABLE II: Assembly task outcomes for the full hand and two ablated configurations. ✓ : success; × : failure.
Fig. 6: In-hand object rotation in simulation and on hardware. Photographs show hardware experiments with a practice golf ball, a pickleball, and a volleyball. Large markers show mean simulation success rates across three training seeds; small markers show results for each seed. Error bars indicate 95% hierarchical bootstrap confidence intervals.
Fig. 7: Response to an applied force with a peak magnitude of 0.75N and a duration of 0.25s during rotation of a 100mm sphere. (a) Success rate for continuous sphere rotation before and after fine-tuning under disturbances from eight directions, with 32 rollouts per direction per seed across three training seeds of the original policies. (b), (c) Keyframes from a selected rollout at 225∘ using the original and fine-tuned policies, respectively. The top and bottom rows show the proposed hand and the LEAP Hand, respectively. Frames show the motion before, during, and after the disturbance. Blue traces show the sphere COM trajectory over the preceding 2.0s ; red arrows indicate the applied force.
A hallmark of human dexterity is the cooperative use of fingers, where different fingers take on distinct yet coordinated roles to accomplish fine manipu- lation, such as capping a pen with the hand that holds it. We study this finger-level coordination through in-hand assembly: mating two rigid objects within a single dexterous hand, with no second arm and no fixture. We present a reinforcement learning formulation to solve this problem in a unified framework, which is driven by a goal relative pose between the two parts. Finger coordination is shaped by a function-based auxiliary reward and regularized toward a single human reference pose, while domain randomization and a fusion of historical proprioception and object observation confer robustness to occlusion-induced estimation noise. The same recipe solves three different assembly tasks (Bottle, Syringe, and Marker). Trained purely in simulation, the policies transfer zero-shot to hardware with a single camera, demonstrating robustness to state-estimation errors caused by oc- clusion. Our experiments also reveal that in-hand assembly places demands on hand morphology and can serve as a benchmark for modern robotic hand systems. Videos and code are available at https://ltbgbird.github.io/in-hand-assembly-page/.
Liuao Pei, Tianyue Wu, Hui Zhang +2
The University of Hong Kong · The Hong Kong University of Science and Technology (Guangzhou) · ETH Zurich +1
This study investigates the kinematic role of palm degrees of freedom (DoF) in enhancing thumb opposability in a five-finger robotic hand. A hand model consisting of a five DoF thumb and four fingers with three to four DoF is analyzed, where palm motion is introduced between adjacent fingers. To quantitatively evaluate thumb-finger interaction, the overlap workspace volume is defined based on voxelized fingertip reachable regions. Seven cases are considered, including configurations with increased total DoF and configurations in which the total DoF is maintained by redistributing DoF from the fingers to the palm. The results show that palm DoF significantly improves opposability, particularly for the ring and little fingers, by repositioning their base locations rather than simply extending their reachable range. However, when the total DoF is constrained, redistributing DoF to the palm leads to trade-offs between overlap workspace expansion and kinematic redundancy. These findings indicate that palm DoF and finger DoF play distinct roles in hand kinematics and should be considered jointly in design. This study provides a quantitative framework for evaluating palm-induced opposability without relying on object or contact models and offers practical design guidelines for incorporating palm motion in robotic hands.
HyoJae Kang, Yeong Jae Park, Hyunmok Jung +2
Advanced Robotics Research Center, Korea Institute of Machinery & Materials (KIMM)
This paper introduces a novel design for a robotic hand based on parallel mechanisms. The proposed hand uses a triple-symmetric Bricard linkage as its reconfigurable palm, enhancing adaptability to objects of varying shapes and sizes. Through topological and dimensional synthesis, the mechanism achieves a well-balanced degree of freedom and link configuration suitable for reconfigurable palm motion, balancing dexterity, stability, and load capacity. Furthermore, kinematic analysis is performed using screw theory and closed-loop constraints, and performance is evaluated based on workspace, stiffness, and motion/force transmission efficiency. Finally, a prototype is developed and tested through a series of grasping experiments, demonstrating the ability to perform stable and efficient manipulation across a wide range of objects. The results validate the effectiveness of the design in improving grasping versatility and operational precision, offering a promising solution for advanced robotic manipulation tasks.
Chunxu Tian, Zhichao Huang, Hongzeng Li +4
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China. · Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.