Slip-Induced Fall Suppression During Cornering for a Remotely Operated Motorcycle with a Rear-Wheel-Swing Mechanism

Tadashi Sumioka; Kazushi Akimoto; Takuya Tsujimura; Sho Takayanagi; Kineo Tomura

cs.ROOct 15, 2026

Slip-Induced Fall Suppression During Cornering for a Remotely Operated Motorcycle with a Rear-Wheel-Swing Mechanism

Authors: Tadashi Sumioka, Kazushi Akimoto, Takuya Tsujimura, Sho Takayanagi, Kineo Tomura

Organizations: Honda R&D Co., Ltd., Innovative Research Excellence, Frontier Robotics, Saitama 3510114, Japan · Honda Motor Co., Ltd.

Abstract

Slip-induced falls when riding motorcycles are difficult to avoid even for expert riders and represent a major cause of single-vehicle accidents. Despite their prevalence, no practical solution has yet been proposed to suppress this phenomenon. We previously introduced a motorcycle model applicable to systems with both front- and rear- wheel steering. In this paper, we extend that model and formulate the suppression of slip-induced falls as an optimization problem that distributes assistive control inputs according to vehicle speed and road surface conditions. To evaluate the proposed method, we developed a remotely operated motorcycle and conducted experiments under two scenarios: slalom driving on a low-friction surface at 5.5 m/s, and turning maneuvers on synthetic ice to simulate driving over manholes on rainy days. The results demonstrate that our approach successfully suppresses falls under these challenging conditions.

Figures & tables

Fig. 1: Motorcycle with rear-wheel swing assist mechanism. This experimental vehicle was developed based on a mass-produced motorcycle.

Symbol	Unit	Description
$m$	kg	Total mass
$h$	m	Height of center of gravity
$I_{x}$	kgm 2	Total roll inertia about center of gravity
$g$	m/s 2	Gravitational acceleration
$\delta_{i}$	rad	Steering angle
$R_{i}$	m	Wheel radius

TABLE I: Definitions of Variables

Fig. 2: Hardware configuration of motorcycle with rear-wheel swing assist mechanism. (a) Left-side view. (b) Rear view. (c) Details of four-bar linkage mechanism. The front-wheel steering has a motor that can control the angular velocity. The rear wheel is swung using a four-bar linkage mechanism, where the length of Link3 is longer than that of Link1; Link2 and Link4 are the same length. The vehicle body is fixed to Link1 and the rear wheel is fixed to Link3. Link1 is connected to the vehicle body at the pivot point. $\delta_{r}$ is the rear-wheel swing angle, which is the same as the rear-wheel roll angle with respect to the vehicle body. Compared with $\theta_{cf}$ and $L_{of}$ , $\theta_{cr}$ and $L_{or}$ are much larger; however, $\delta_{r}$ can still be regarded as the rear‑wheel steering angle, in a broad sense, based on the same definition as that of the front wheel.

Fig. 3: Diagram of overall control scheme. The left stick of the wireless controller was configured such that, when fully tilted to the left, the command becomes $P_{1yd}=|P_{1yd_{\lim}}|$ , and when fully tilted to the right, it becomes $P_{1yd}=-|P_{1yd_{\lim}}|$ . The lateral analog values of the left stick were linearly interpolated between these limits and transmitted to the onboard controller. Similarly, when the left stick is pushed fully downward, the vertical analog values of the left stick were linearly interpolated so that a larger front‑brake‑lever command is generated, and this signal was transmitted to the onboard controller. Furthermore, the vertical analog values of the right stick were configured such that upward input corresponds to a positive motor torque and downward input corresponds to a negative motor torque, and this command was also transmitted to the onboard controller.

Fig. 4: Lateral acceleration generated when steering front and rear wheels at 0.524 rad and 0.175 rad, respectively, with respect to straight-ahead driving state.

Fig. 5: Snapshot of experiment of low- $\mu$ road driving. A slalom experiment was conducted on wet ceramic tiles. Slip was induced by braking or driving at a turning point of the slalom run.

Fig. 6: Snapshots of experiment using synthetic ice. The coefficient of friction of the strip of synthetic ice was approximately 0.36.

Fig. 7: Results of low- $\mu$ road slalom test. (a) Longitudinal velocity. (b) Vehicle body roll angle. (c) Vehicle body yaw rate. (d) Side-slip angle of center of gravity. (e) Front- and rear-wheel steering angles. Slips occurred at around 10, 15, 28, and 37 s.

Fig. 8: Results of front-wheel braking during low- $\mu$ slalom test. (a) Longitudinal velocity. (b) Vehicle body roll angle. (c) Vehicle body yaw rate. (d) Side-slip angle of center of gravity. (e) Front- and rear-wheel steering angles. Slips occurred at around 43 s.

Fig. 9: Results of rear-wheel braking during slalom test on low- $\mu$ road. (a) Longitudinal velocity. (b) Vehicle body roll angle. (c) Vehicle body yaw rate. (d) Side-slip angle of center of gravity. (e) Front- and rear-wheel steering angles. Slips occurred at around 19 s.

Fig. 10: Results of rear-wheel driving during low- $\mu$ slalom test. (a) Longitudinal velocity. (b) Vehicle body roll angle. (c) Vehicle body yaw rate. (d) Side-slip angle of center of gravity. (e) Front- and rear-wheel steering angles. Slips occurred at around 50 s.

Fig. 11: Results of turning on strip of synthetic ice while braking front wheel. (a) Longitudinal velocity. (b) Vehicle body roll angle. (c) Vehicle body yaw rate. (d) Side-slip angle of center of gravity. (e) Front- and rear-wheel steering angles. Slips occurred at around 14 s.

Appendix figures & tables2 assets

Supplementary material from the paper’s appendix.

Appendix

Fig. 12: Results of remotely operated driving in an open area without a predefined course on a dry asphalt road surface. (a) Longitudinal velocity. (b) Vehicle body roll angle. (c) Vehicle body yaw rate. (d) Side-slip angle of center of gravity. (e) Front- and rear-wheel steering angles. (f) Trajectory of center of gravity. $\bar{\mu}=1$ was set.

Fig. 13: Results extracted around 26 s in Fig. 12 (around position

P1

in Fig. 12 (f)). During right turning with a vehicle lean angle of approximately 0.1 rad at a speed of 4.9 m/s, a small positive

\beta

was observed.

Vehicle Dynamics

Vehicle dynamics studies how vehicles move and respond to forces from tires, terrain, aerodynamics, and control inputs.

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Stable Walking for Bipedal Locomotion under Foot-Slip via Virtual Nonholonomic Constraints

Leonardo Colombo, Álvaro Rodríguez Abella, Alexandre Anahory Simoes, Anthony Bloch

Centre for Automation and Robotics (CSIC-UPM), Ctra. M300 Campo Real, Km 0,200, Arganda del Rey - 28500 Madrid, Spain. · the Department of Applied Mathematics, Comillas Pontifical University, Madrid, 28015 - Madrid, Spain. · School of Science and Technology, IE University, Madrid, Spain.+1

Legged Robotics Humanoid Robot Locomotion

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Foot slip is a major source of instability in bipedal locomotion on low-friction or uncertain terrain. Standard control approaches typically assume no-slip contact and therefore degrade when slip occurs. We propose a control framework that explicitly incorporates slip into the locomotion model through virtual nonholonomic constraints, which regulate the tangential stance-foot velocity while remaining compatible with the virtual holonomic constraints used to generate the walking gait. The resulting closed-loop system is formulated as a hybrid dynamical system with continuous swing dynamics and discrete impact events. A nonlinear feedback law enforces both classes of constraints and yields a slip-compatible hybrid zero dynamics manifold for the reduced-order locomotion dynamics. Stability of periodic walking gaits is characterized through the associated Poincaré map, and numerical results illustrate stabilization under slip conditions.

Abstract

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